update base models

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only}/.hydra/config.yaml

@@ -20,12 +20,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C1
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
     type: encoder_classification
     num_labels: 6
     output_dir: ./results/
     logging_dir: ./logs/
-    best_model_dir: ./results/best_model
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only}/.hydra/hydra.yaml

@@ -1,6 +1,6 @@
 hydra:
   run:
-    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    dir: inference_output/2025-07-10/00-30-43
   sweep:
     dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
     subdir: ${hydra.job.num}
@@ -110,13 +110,14 @@ hydra:
   output_subdir: .hydra
   overrides:
     hydra:
+    - hydra.run.dir=inference_output/2025-07-10/00-30-43
     - hydra.mode=RUN
     task:
-    - experiments=base_models/C3
+    - experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
   job:
     name: run_inference_experiment
     chdir: null
-    override_dirname: experiments=base_models/C3
+    override_dirname: experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
     id: ???
     num: ???
     config_name: config
@@ -141,9 +142,9 @@ hydra:
     - path: ''
       schema: structured
       provider: schema
-    output_dir: /workspace/jbcs2025/outputs/2025-06-30/23-55-38
+    output_dir: /workspace/jbcs2025/inference_output/2025-07-10/00-30-43
     choices:
-      experiments: base_models/C3
+      experiments: temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
       hydra/env: default
       hydra/callbacks: null
       hydra/job_logging: default

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/.hydra/overrides.yaml

@@ -0,0 +1 @@
+- experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/bootstrap_confidence_intervals.csv

@@ -0,0 +1,2 @@
+experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
+jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only,2025-07-10 00:30:49,0.5958170760500687,0.5050211692312583,0.6837528419789116,0.17873167274765334,0.40342568031357534,0.29995035727435776,0.5366313750336464,0.23668101775928868,0.5194883832140518,0.43316166991474553,0.6049356141130027,0.17177394419825714

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only}/evaluation_results.csv

@@ -1,2 +1,2 @@
-accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
-0.644927536231884,26.37521893583148,0.6742722265932337,0.007246376811594235,0.44138845418188133,0.644927536231884,0.6413771139990777,0,137,0,1,0,138,0,0,5,123,5,5,56,52,20,10,22,79,8,29,6,112,16,4,2025-06-30 23:51:41,jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only
+accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
+0.5144927536231884,31.20757990421976,0.5980582524271845,0.007246376811594235,0.37408319849679,0.5144927536231884,0.51825410693578,0,137,0,1,0,138,0,0,5,115,13,5,25,65,7,41,34,57,30,17,7,111,17,3,2025-07-10 00:30:49,jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only}/run_inference_experiment.log

@@ -1,5 +1,5 @@
-[2025-06-30 23:51:41,386][__main__][INFO] - Starting inference experiment
-[2025-06-30 23:51:41,387][__main__][INFO] - cache_dir: /tmp/
+[2025-07-10 00:30:49,125][__main__][INFO] - Starting inference experiment
+[2025-07-10 00:30:49,127][__main__][INFO] - cache_dir: /tmp/
 dataset:
   name: kamel-usp/aes_enem_dataset
   split: JBCS2025
@@ -21,12 +21,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C1
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
     type: encoder_classification
     num_labels: 6
     output_dir: ./results/
     logging_dir: ./logs/
-    best_model_dir: ./results/best_model
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:
@@ -41,9 +41,9 @@ experiments:
     gradient_accumulation_steps: 1
     gradient_checkpointing: false
 
-[2025-06-30 23:51:41,389][__main__][INFO] - Running inference with fine-tuned HF model
-[2025-06-30 23:51:46,517][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:51:46,518][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:30:49,129][__main__][INFO] - Running inference with fine-tuned HF model
+[2025-07-10 00:30:53,775][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:30:53,776][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -68,20 +68,14 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:51:46,722][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-30 23:51:46,722][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-30 23:51:46,722][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-30 23:51:46,722][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-30 23:51:46,722][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-30 23:51:46,722][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-30 23:51:46,722][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:51:46,723][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:30:54,000][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:30:54,000][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -106,14 +100,20 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:51:46,749][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:51:46,749][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:30:54,217][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
+[2025-07-10 00:30:54,217][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
+[2025-07-10 00:30:54,217][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
+[2025-07-10 00:30:54,217][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
+[2025-07-10 00:30:54,217][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
+[2025-07-10 00:30:54,218][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
+[2025-07-10 00:30:54,218][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:30:54,218][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -138,18 +138,73 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:51:46,765][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True; Use Full Context: False
-[2025-06-30 23:51:46,816][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C1
-[2025-06-30 23:51:46,816][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C1
-[2025-06-30 23:51:47,523][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
-[2025-06-30 23:51:47,758][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C1/snapshots/1ad2e0f61009276ce3c1d23b24b6f55e0eb102d8/config.json
-[2025-06-30 23:51:47,758][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:30:54,254][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:30:54,255][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 29794
+}
+
+[2025-07-10 00:30:54,274][__main__][INFO] - Tokenizer function parameters- Padding:longest; Truncation: True; Use Full Context: False
+[2025-07-10 00:30:54,745][__main__][INFO] - 
+Token statistics for 'train' split:
+[2025-07-10 00:30:54,745][__main__][INFO] -   Total examples: 500
+[2025-07-10 00:30:54,745][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:30:54,746][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:30:54,746][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:30:54,746][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:30:54,858][__main__][INFO] - 
+Token statistics for 'validation' split:
+[2025-07-10 00:30:54,858][__main__][INFO] -   Total examples: 132
+[2025-07-10 00:30:54,858][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:30:54,858][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:30:54,858][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:30:54,858][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:30:54,966][__main__][INFO] - 
+Token statistics for 'test' split:
+[2025-07-10 00:30:54,966][__main__][INFO] -   Total examples: 138
+[2025-07-10 00:30:54,966][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:30:54,966][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:30:54,966][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:30:54,966][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:30:54,966][__main__][INFO] - If token statistics are the same (max, avg, min) keep in mind that this is due to batched tokenization and padding.
+[2025-07-10 00:30:54,966][__main__][INFO] - Model max length: 512. If it is the same as stats, then there is a high chance that sequences are being truncated.
+[2025-07-10 00:30:54,967][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
+[2025-07-10 00:30:54,967][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only
+[2025-07-10 00:30:55,690][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
+[2025-07-10 00:30:55,962][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only/snapshots/7ae84ea1c7bb39379d09e28c0d1de9ed08d5c308/config.json
+[2025-07-10 00:30:55,963][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForSequenceClassification"
   ],
@@ -190,37 +245,36 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:51:47,903][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C1/snapshots/1ad2e0f61009276ce3c1d23b24b6f55e0eb102d8/model.safetensors
-[2025-06-30 23:51:47,903][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
-[2025-06-30 23:51:47,903][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-30 23:51:48,334][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
+[2025-07-10 00:30:56,173][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only/snapshots/7ae84ea1c7bb39379d09e28c0d1de9ed08d5c308/model.safetensors
+[2025-07-10 00:30:56,173][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
+[2025-07-10 00:30:56,173][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
+[2025-07-10 00:30:57,523][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
 
-[2025-06-30 23:51:48,334][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bertimbau_base-C1.
+[2025-07-10 00:30:57,523][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only.
 If your task is similar to the task the model of the checkpoint was trained on, you can already use BertForSequenceClassification for predictions without further training.
-[2025-06-30 23:51:48,339][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-30 23:51:48,372][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
-[2025-06-30 23:51:48,376][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-30 23:51:48,396][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-30 23:51:51,813][__main__][INFO] - Running inference on test dataset
-[2025-06-30 23:51:51,814][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: supporting_text, prompt, grades, reference, essay_text, essay_year, id, id_prompt. If supporting_text, prompt, grades, reference, essay_text, essay_year, id, id_prompt are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-30 23:51:51,818][transformers.trainer][INFO] - 
+[2025-07-10 00:30:57,533][transformers.training_args][INFO] - PyTorch: setting up devices
+[2025-07-10 00:30:57,557][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+[2025-07-10 00:30:57,564][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
+[2025-07-10 00:30:57,589][transformers.trainer][INFO] - Using auto half precision backend
+[2025-07-10 00:31:00,916][__main__][INFO] - Running inference on test dataset
+[2025-07-10 00:31:00,917][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: supporting_text, id, prompt, reference, essay_year, id_prompt, grades, essay_text. If supporting_text, id, prompt, reference, essay_year, id_prompt, grades, essay_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
+[2025-07-10 00:31:00,923][transformers.trainer][INFO] - 
 ***** Running Prediction *****
-[2025-06-30 23:51:51,818][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-30 23:51:51,818][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-30 23:51:52,209][__main__][INFO] - Inference results saved to jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only_inference_results.jsonl
-[2025-06-30 23:51:52,214][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
-[2025-06-30 23:53:26,617][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
-[2025-06-30 23:53:26,617][__main__][INFO] - Bootstrap Confidence Intervals (95%):
-[2025-06-30 23:53:26,617][__main__][INFO] -   QWK: 0.6727 [0.5787, 0.7587]
-[2025-06-30 23:53:26,617][__main__][INFO] -   Macro_F1: 0.4757 [0.3600, 0.6232]
-[2025-06-30 23:53:26,617][__main__][INFO] -   Weighted_F1: 0.6413 [0.5564, 0.7242]
-[2025-06-30 23:53:26,617][__main__][INFO] - Inference results: {'accuracy': 0.644927536231884, 'RMSE': 26.37521893583148, 'QWK': 0.6742722265932337, 'HDIV': 0.007246376811594235, 'Macro_F1': 0.44138845418188133, 'Micro_F1': 0.644927536231884, 'Weighted_F1': 0.6413771139990777, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(138), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(5), 'TN_2': np.int64(123), 'FP_2': np.int64(5), 'FN_2': np.int64(5), 'TP_3': np.int64(56), 'TN_3': np.int64(52), 'FP_3': np.int64(20), 'FN_3': np.int64(10), 'TP_4': np.int64(22), 'TN_4': np.int64(79), 'FP_4': np.int64(8), 'FN_4': np.int64(29), 'TP_5': np.int64(6), 'TN_5': np.int64(112), 'FP_5': np.int64(16), 'FN_5': np.int64(4)}
-[2025-06-30 23:53:26,617][__main__][INFO] - Inference experiment completed
+[2025-07-10 00:31:00,924][transformers.trainer][INFO] -   Num examples = 138
+[2025-07-10 00:31:00,924][transformers.trainer][INFO] -   Batch size = 16
+[2025-07-10 00:31:01,737][__main__][INFO] - Inference results saved to jbcs2025_bert-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only_inference_results.jsonl
+[2025-07-10 00:31:01,738][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
+[2025-07-10 00:33:14,131][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
+[2025-07-10 00:33:14,131][__main__][INFO] - Bootstrap Confidence Intervals (95%):
+[2025-07-10 00:33:14,131][__main__][INFO] -   QWK: 0.5958 [0.5050, 0.6838]
+[2025-07-10 00:33:14,131][__main__][INFO] -   Macro_F1: 0.4034 [0.3000, 0.5366]
+[2025-07-10 00:33:14,131][__main__][INFO] -   Weighted_F1: 0.5195 [0.4332, 0.6049]
+[2025-07-10 00:33:14,132][__main__][INFO] - Inference results: {'accuracy': 0.5144927536231884, 'RMSE': 31.20757990421976, 'QWK': 0.5980582524271845, 'HDIV': 0.007246376811594235, 'Macro_F1': 0.37408319849679, 'Micro_F1': 0.5144927536231884, 'Weighted_F1': 0.51825410693578, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(138), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(5), 'TN_2': np.int64(115), 'FP_2': np.int64(13), 'FN_2': np.int64(5), 'TP_3': np.int64(25), 'TN_3': np.int64(65), 'FP_3': np.int64(7), 'FN_3': np.int64(41), 'TP_4': np.int64(34), 'TN_4': np.int64(57), 'FP_4': np.int64(30), 'FN_4': np.int64(17), 'TP_5': np.int64(7), 'TN_5': np.int64(111), 'FP_5': np.int64(17), 'FN_5': np.int64(3)}
+[2025-07-10 00:33:14,133][__main__][INFO] - Inference experiment completed

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only}/.hydra/config.yaml

@@ -20,12 +20,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C2
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/mbert_base/C2
-    logging_dir: ./logs/mbert_base/C2
-    best_model_dir: ./results/mbert_base/C2/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only}/.hydra/hydra.yaml

@@ -1,6 +1,6 @@
 hydra:
   run:
-    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    dir: inference_output/2025-07-10/00-33-18
   sweep:
     dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
     subdir: ${hydra.job.num}
@@ -110,13 +110,14 @@ hydra:
   output_subdir: .hydra
   overrides:
     hydra:
+    - hydra.run.dir=inference_output/2025-07-10/00-33-18
     - hydra.mode=RUN
     task:
-    - experiments=base_models/C1
+    - experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
   job:
     name: run_inference_experiment
     chdir: null
-    override_dirname: experiments=base_models/C1
+    override_dirname: experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
     id: ???
     num: ???
     config_name: config
@@ -141,9 +142,9 @@ hydra:
     - path: ''
       schema: structured
       provider: schema
-    output_dir: /workspace/jbcs2025/outputs/2025-06-30/23-51-41
+    output_dir: /workspace/jbcs2025/inference_output/2025-07-10/00-33-18
     choices:
-      experiments: base_models/C1
+      experiments: temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
       hydra/env: default
       hydra/callbacks: null
       hydra/job_logging: default

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only/.hydra/overrides.yaml

@@ -0,0 +1 @@
+- experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only}/bootstrap_confidence_intervals.csv

@@ -1,2 +1,2 @@
 experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
-jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only,2025-06-30 23:51:41,0.6726698793738349,0.5786694701512399,0.7587417074110893,0.18007223725984933,0.4756728951042896,0.36004609141863914,0.6232464233862081,0.2632003319675689,0.6413009122974154,0.556374600523932,0.7241688998827073,0.16779429935877532
+jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only,2025-07-10 00:33:24,0.34458059523975704,0.1923734854942415,0.48687400610895387,0.2945005206147124,0.2628237843641066,0.18370517105663375,0.3615635882194743,0.17785841716284057,0.34854638571439245,0.2694481582021241,0.4294118073125417,0.1599636491104176

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only/evaluation_results.csv

@@ -0,0 +1,2 @@
+accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
+0.34782608695652173,63.519938670433646,0.3477835723598436,0.1159420289855072,0.24903083028083028,0.34782608695652173,0.34937224611137657,0,137,0,1,17,70,33,18,1,124,9,4,19,66,21,32,6,92,20,20,5,111,7,15,2025-07-10 00:33:24,jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only}/run_inference_experiment.log

@@ -1,5 +1,5 @@
-[2025-06-30 23:55:38,582][__main__][INFO] - Starting inference experiment
-[2025-06-30 23:55:38,583][__main__][INFO] - cache_dir: /tmp/
+[2025-07-10 00:33:24,293][__main__][INFO] - Starting inference experiment
+[2025-07-10 00:33:24,295][__main__][INFO] - cache_dir: /tmp/
 dataset:
   name: kamel-usp/aes_enem_dataset
   split: JBCS2025
@@ -21,16 +21,16 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C3
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/mbert_base/C3
-    logging_dir: ./logs/mbert_base/C3
-    best_model_dir: ./results/mbert_base/C3/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:
-    grade_index: 2
+    grade_index: 1
     use_full_context: false
   training_params:
     weight_decay: 0.01
@@ -41,9 +41,9 @@ experiments:
     gradient_accumulation_steps: 1
     gradient_checkpointing: false
 
-[2025-06-30 23:55:38,585][__main__][INFO] - Running inference with fine-tuned HF model
-[2025-06-30 23:55:44,174][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:55:44,176][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:33:24,297][__main__][INFO] - Running inference with fine-tuned HF model
+[2025-07-10 00:33:29,586][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:33:29,587][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -68,20 +68,14 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:55:44,390][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-30 23:55:44,390][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-30 23:55:44,390][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-30 23:55:44,390][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-30 23:55:44,390][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-30 23:55:44,391][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-30 23:55:44,391][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:55:44,391][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:33:29,802][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:33:29,803][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -106,14 +100,20 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:55:44,421][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:55:44,422][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:33:29,988][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
+[2025-07-10 00:33:29,988][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
+[2025-07-10 00:33:29,988][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
+[2025-07-10 00:33:29,988][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
+[2025-07-10 00:33:29,988][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
+[2025-07-10 00:33:29,988][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
+[2025-07-10 00:33:29,988][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:33:29,989][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -138,18 +138,73 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:55:44,438][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True; Use Full Context: False
-[2025-06-30 23:55:44,646][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C3
-[2025-06-30 23:55:44,646][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C3
-[2025-06-30 23:55:45,504][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
-[2025-06-30 23:55:46,269][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C3/snapshots/bad03f1db697f1fb612e4d74bb55d6f0e8cd7a16/config.json
-[2025-06-30 23:55:46,270][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:33:30,019][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:33:30,019][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 29794
+}
+
+[2025-07-10 00:33:30,037][__main__][INFO] - Tokenizer function parameters- Padding:longest; Truncation: True; Use Full Context: False
+[2025-07-10 00:33:30,459][__main__][INFO] - 
+Token statistics for 'train' split:
+[2025-07-10 00:33:30,459][__main__][INFO] -   Total examples: 500
+[2025-07-10 00:33:30,459][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:33:30,459][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:33:30,459][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:33:30,459][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:33:30,550][__main__][INFO] - 
+Token statistics for 'validation' split:
+[2025-07-10 00:33:30,550][__main__][INFO] -   Total examples: 132
+[2025-07-10 00:33:30,550][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:33:30,550][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:33:30,550][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:33:30,550][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:33:30,644][__main__][INFO] - 
+Token statistics for 'test' split:
+[2025-07-10 00:33:30,644][__main__][INFO] -   Total examples: 138
+[2025-07-10 00:33:30,644][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:33:30,644][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:33:30,644][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:33:30,644][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:33:30,644][__main__][INFO] - If token statistics are the same (max, avg, min) keep in mind that this is due to batched tokenization and padding.
+[2025-07-10 00:33:30,644][__main__][INFO] - Model max length: 512. If it is the same as stats, then there is a high chance that sequences are being truncated.
+[2025-07-10 00:33:30,645][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
+[2025-07-10 00:33:30,645][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only
+[2025-07-10 00:33:31,659][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
+[2025-07-10 00:33:32,456][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only/snapshots/05b2dbb38d9087976e945d31d5e052862b434715/config.json
+[2025-07-10 00:33:32,457][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForSequenceClassification"
   ],
@@ -190,37 +245,36 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:55:59,432][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C3/snapshots/bad03f1db697f1fb612e4d74bb55d6f0e8cd7a16/model.safetensors
-[2025-06-30 23:55:59,433][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
-[2025-06-30 23:55:59,433][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-30 23:55:59,824][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
+[2025-07-10 00:33:41,347][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only/snapshots/05b2dbb38d9087976e945d31d5e052862b434715/model.safetensors
+[2025-07-10 00:33:41,348][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
+[2025-07-10 00:33:41,349][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
+[2025-07-10 00:33:41,748][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
 
-[2025-06-30 23:55:59,825][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bertimbau_base-C3.
+[2025-07-10 00:33:41,748][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only.
 If your task is similar to the task the model of the checkpoint was trained on, you can already use BertForSequenceClassification for predictions without further training.
-[2025-06-30 23:55:59,830][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-30 23:55:59,868][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
-[2025-06-30 23:55:59,872][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-30 23:55:59,891][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-30 23:56:03,371][__main__][INFO] - Running inference on test dataset
-[2025-06-30 23:56:03,372][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: reference, essay_text, essay_year, id, supporting_text, id_prompt, grades, prompt. If reference, essay_text, essay_year, id, supporting_text, id_prompt, grades, prompt are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-30 23:56:03,376][transformers.trainer][INFO] - 
+[2025-07-10 00:33:41,758][transformers.training_args][INFO] - PyTorch: setting up devices
+[2025-07-10 00:33:41,783][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+[2025-07-10 00:33:41,791][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
+[2025-07-10 00:33:41,818][transformers.trainer][INFO] - Using auto half precision backend
+[2025-07-10 00:33:45,118][__main__][INFO] - Running inference on test dataset
+[2025-07-10 00:33:45,119][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: reference, prompt, essay_year, id_prompt, grades, essay_text, supporting_text, id. If reference, prompt, essay_year, id_prompt, grades, essay_text, supporting_text, id are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
+[2025-07-10 00:33:45,125][transformers.trainer][INFO] - 
 ***** Running Prediction *****
-[2025-06-30 23:56:03,376][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-30 23:56:03,377][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-30 23:56:03,760][__main__][INFO] - Inference results saved to jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only_inference_results.jsonl
-[2025-06-30 23:56:03,767][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
-[2025-06-30 23:57:39,277][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
-[2025-06-30 23:57:39,277][__main__][INFO] - Bootstrap Confidence Intervals (95%):
-[2025-06-30 23:57:39,277][__main__][INFO] -   QWK: 0.3443 [0.2085, 0.4793]
-[2025-06-30 23:57:39,277][__main__][INFO] -   Macro_F1: 0.2754 [0.2026, 0.3652]
-[2025-06-30 23:57:39,277][__main__][INFO] -   Weighted_F1: 0.3357 [0.2573, 0.4166]
-[2025-06-30 23:57:39,277][__main__][INFO] - Inference results: {'accuracy': 0.37681159420289856, 'RMSE': 52.64042641120627, 'QWK': 0.3452054794520547, 'HDIV': 0.09420289855072461, 'Macro_F1': 0.25943499029705924, 'Micro_F1': 0.37681159420289856, 'Weighted_F1': 0.33380294701134283, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(109), 'FP_1': np.int64(0), 'FN_1': np.int64(29), 'TP_2': np.int64(13), 'TN_2': np.int64(101), 'FP_2': np.int64(19), 'FN_2': np.int64(5), 'TP_3': np.int64(20), 'TN_3': np.int64(71), 'FP_3': np.int64(22), 'FN_3': np.int64(25), 'TP_4': np.int64(17), 'TN_4': np.int64(67), 'FP_4': np.int64(33), 'FN_4': np.int64(21), 'TP_5': np.int64(2), 'TN_5': np.int64(119), 'FP_5': np.int64(12), 'FN_5': np.int64(5)}
-[2025-06-30 23:57:39,277][__main__][INFO] - Inference experiment completed
+[2025-07-10 00:33:45,125][transformers.trainer][INFO] -   Num examples = 138
+[2025-07-10 00:33:45,126][transformers.trainer][INFO] -   Batch size = 16
+[2025-07-10 00:33:45,907][__main__][INFO] - Inference results saved to jbcs2025_bert-base-portuguese-cased-encoder_classification-C2-essay_only-encoder_classification-C2-essay_only_inference_results.jsonl
+[2025-07-10 00:33:45,908][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
+[2025-07-10 00:35:53,783][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
+[2025-07-10 00:35:53,783][__main__][INFO] - Bootstrap Confidence Intervals (95%):
+[2025-07-10 00:35:53,783][__main__][INFO] -   QWK: 0.3446 [0.1924, 0.4869]
+[2025-07-10 00:35:53,783][__main__][INFO] -   Macro_F1: 0.2628 [0.1837, 0.3616]
+[2025-07-10 00:35:53,783][__main__][INFO] -   Weighted_F1: 0.3485 [0.2694, 0.4294]
+[2025-07-10 00:35:53,783][__main__][INFO] - Inference results: {'accuracy': 0.34782608695652173, 'RMSE': 63.519938670433646, 'QWK': 0.3477835723598436, 'HDIV': 0.1159420289855072, 'Macro_F1': 0.24903083028083028, 'Micro_F1': 0.34782608695652173, 'Weighted_F1': 0.34937224611137657, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(17), 'TN_1': np.int64(70), 'FP_1': np.int64(33), 'FN_1': np.int64(18), 'TP_2': np.int64(1), 'TN_2': np.int64(124), 'FP_2': np.int64(9), 'FN_2': np.int64(4), 'TP_3': np.int64(19), 'TN_3': np.int64(66), 'FP_3': np.int64(21), 'FN_3': np.int64(32), 'TP_4': np.int64(6), 'TN_4': np.int64(92), 'FP_4': np.int64(20), 'FN_4': np.int64(20), 'TP_5': np.int64(5), 'TN_5': np.int64(111), 'FP_5': np.int64(7), 'FN_5': np.int64(15)}
+[2025-07-10 00:35:53,783][__main__][INFO] - Inference experiment completed

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only}/.hydra/config.yaml

@@ -20,12 +20,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C3
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/mbert_base/C3
-    logging_dir: ./logs/mbert_base/C3
-    best_model_dir: ./results/mbert_base/C3/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only}/.hydra/hydra.yaml

@@ -1,6 +1,6 @@
 hydra:
   run:
-    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    dir: inference_output/2025-07-10/00-35-58
   sweep:
     dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
     subdir: ${hydra.job.num}
@@ -110,13 +110,14 @@ hydra:
   output_subdir: .hydra
   overrides:
     hydra:
+    - hydra.run.dir=inference_output/2025-07-10/00-35-58
     - hydra.mode=RUN
     task:
-    - experiments=base_models/C2
+    - experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
   job:
     name: run_inference_experiment
     chdir: null
-    override_dirname: experiments=base_models/C2
+    override_dirname: experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
     id: ???
     num: ???
     config_name: config
@@ -141,9 +142,9 @@ hydra:
     - path: ''
       schema: structured
       provider: schema
-    output_dir: /workspace/jbcs2025/outputs/2025-06-30/23-53-32
+    output_dir: /workspace/jbcs2025/inference_output/2025-07-10/00-35-58
     choices:
-      experiments: base_models/C2
+      experiments: temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
       hydra/env: default
       hydra/callbacks: null
       hydra/job_logging: default

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only/.hydra/overrides.yaml

@@ -0,0 +1 @@
+- experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only}/bootstrap_confidence_intervals.csv

@@ -1,2 +1,2 @@
 experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
-jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only,2025-06-30 23:55:38,0.3442546344979946,0.20848447033589465,0.47933895194622367,0.270854481610329,0.27540748660610137,0.20263838658028993,0.36522069296926984,0.1625823063889799,0.33565410439112764,0.25734749784644845,0.4165551974170723,0.15920769957062386
+jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only,2025-07-10 00:36:03,0.34693349366334814,0.1990600571882507,0.4852465288821567,0.286186471693906,0.23118176088630918,0.16413028510813224,0.3143442286349,0.15021394352676778,0.2678663440815833,0.19402110750115098,0.34536043688479334,0.15133932938364236

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only}/evaluation_results.csv

@@ -1,2 +1,2 @@
-accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
-0.644927536231884,26.37521893583148,0.6258134490238612,0.007246376811594235,0.36114488348530904,0.644927536231884,0.6545879036165807,0,137,0,1,0,137,0,1,5,118,11,4,51,49,13,25,30,74,18,16,3,126,7,2,2025-06-30 23:57:45,jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only
+accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
+0.3115942028985507,51.07539184552491,0.3491384731480316,0.050724637681159424,0.21826640792158034,0.3115942028985507,0.26630624081898446,0,137,0,1,0,107,2,29,14,94,26,4,18,57,36,27,9,81,19,29,2,119,12,5,2025-07-10 00:36:03,jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only}/run_inference_experiment.log

@@ -1,5 +1,5 @@
-[2025-06-30 23:53:32,300][__main__][INFO] - Starting inference experiment
-[2025-06-30 23:53:32,301][__main__][INFO] - cache_dir: /tmp/
+[2025-07-10 00:36:03,801][__main__][INFO] - Starting inference experiment
+[2025-07-10 00:36:03,803][__main__][INFO] - cache_dir: /tmp/
 dataset:
   name: kamel-usp/aes_enem_dataset
   split: JBCS2025
@@ -21,16 +21,16 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C2
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/mbert_base/C2
-    logging_dir: ./logs/mbert_base/C2
-    best_model_dir: ./results/mbert_base/C2/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:
-    grade_index: 1
+    grade_index: 2
     use_full_context: false
   training_params:
     weight_decay: 0.01
@@ -41,9 +41,9 @@ experiments:
     gradient_accumulation_steps: 1
     gradient_checkpointing: false
 
-[2025-06-30 23:53:32,303][__main__][INFO] - Running inference with fine-tuned HF model
-[2025-06-30 23:53:37,072][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:53:37,073][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:36:03,805][__main__][INFO] - Running inference with fine-tuned HF model
+[2025-07-10 00:36:09,107][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:36:09,108][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -68,20 +68,14 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:53:37,279][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-30 23:53:37,279][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-30 23:53:37,279][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-30 23:53:37,279][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-30 23:53:37,279][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-30 23:53:37,279][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-30 23:53:37,279][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:53:37,280][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:36:09,328][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:36:09,329][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -106,14 +100,20 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:53:37,305][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:53:37,305][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:36:09,524][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
+[2025-07-10 00:36:09,524][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
+[2025-07-10 00:36:09,524][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
+[2025-07-10 00:36:09,524][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
+[2025-07-10 00:36:09,524][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
+[2025-07-10 00:36:09,524][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
+[2025-07-10 00:36:09,525][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:36:09,525][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -138,18 +138,73 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:53:37,322][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True; Use Full Context: False
-[2025-06-30 23:53:37,526][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C2
-[2025-06-30 23:53:37,526][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C2
-[2025-06-30 23:53:38,363][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
-[2025-06-30 23:53:39,154][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C2/snapshots/3afae7b80c36bf0042b19778620a0ad1135b7135/config.json
-[2025-06-30 23:53:39,155][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:36:09,555][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:36:09,556][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 29794
+}
+
+[2025-07-10 00:36:09,573][__main__][INFO] - Tokenizer function parameters- Padding:longest; Truncation: True; Use Full Context: False
+[2025-07-10 00:36:09,998][__main__][INFO] - 
+Token statistics for 'train' split:
+[2025-07-10 00:36:09,998][__main__][INFO] -   Total examples: 500
+[2025-07-10 00:36:09,998][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:36:09,998][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:36:09,998][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:36:09,998][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:36:10,092][__main__][INFO] - 
+Token statistics for 'validation' split:
+[2025-07-10 00:36:10,092][__main__][INFO] -   Total examples: 132
+[2025-07-10 00:36:10,092][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:36:10,092][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:36:10,092][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:36:10,092][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:36:10,186][__main__][INFO] - 
+Token statistics for 'test' split:
+[2025-07-10 00:36:10,186][__main__][INFO] -   Total examples: 138
+[2025-07-10 00:36:10,186][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:36:10,186][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:36:10,186][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:36:10,186][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:36:10,186][__main__][INFO] - If token statistics are the same (max, avg, min) keep in mind that this is due to batched tokenization and padding.
+[2025-07-10 00:36:10,186][__main__][INFO] - Model max length: 512. If it is the same as stats, then there is a high chance that sequences are being truncated.
+[2025-07-10 00:36:10,187][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
+[2025-07-10 00:36:10,187][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only
+[2025-07-10 00:36:11,179][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
+[2025-07-10 00:36:11,981][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only/snapshots/b3bbed41224b673570856cd0c37769f629b1161a/config.json
+[2025-07-10 00:36:11,982][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForSequenceClassification"
   ],
@@ -190,37 +245,36 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:53:51,890][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C2/snapshots/3afae7b80c36bf0042b19778620a0ad1135b7135/model.safetensors
-[2025-06-30 23:53:51,891][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
-[2025-06-30 23:53:51,891][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-30 23:53:52,245][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
+[2025-07-10 00:36:20,667][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only/snapshots/b3bbed41224b673570856cd0c37769f629b1161a/model.safetensors
+[2025-07-10 00:36:20,668][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
+[2025-07-10 00:36:20,668][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
+[2025-07-10 00:36:21,051][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
 
-[2025-06-30 23:53:52,245][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bertimbau_base-C2.
+[2025-07-10 00:36:21,051][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only.
 If your task is similar to the task the model of the checkpoint was trained on, you can already use BertForSequenceClassification for predictions without further training.
-[2025-06-30 23:53:52,251][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-30 23:53:52,307][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
-[2025-06-30 23:53:52,312][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-30 23:53:52,330][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-30 23:53:55,801][__main__][INFO] - Running inference on test dataset
-[2025-06-30 23:53:55,802][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id, reference, essay_year, supporting_text, prompt, grades, essay_text, id_prompt. If id, reference, essay_year, supporting_text, prompt, grades, essay_text, id_prompt are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-30 23:53:55,806][transformers.trainer][INFO] - 
+[2025-07-10 00:36:21,060][transformers.training_args][INFO] - PyTorch: setting up devices
+[2025-07-10 00:36:21,082][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+[2025-07-10 00:36:21,089][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
+[2025-07-10 00:36:21,117][transformers.trainer][INFO] - Using auto half precision backend
+[2025-07-10 00:36:24,486][__main__][INFO] - Running inference on test dataset
+[2025-07-10 00:36:24,487][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id_prompt, reference, prompt, essay_year, id, essay_text, grades, supporting_text. If id_prompt, reference, prompt, essay_year, id, essay_text, grades, supporting_text are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
+[2025-07-10 00:36:24,493][transformers.trainer][INFO] - 
 ***** Running Prediction *****
-[2025-06-30 23:53:55,806][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-30 23:53:55,806][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-30 23:53:56,214][__main__][INFO] - Inference results saved to jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only_inference_results.jsonl
-[2025-06-30 23:53:56,220][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
-[2025-06-30 23:55:32,845][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
-[2025-06-30 23:55:32,845][__main__][INFO] - Bootstrap Confidence Intervals (95%):
-[2025-06-30 23:55:32,845][__main__][INFO] -   QWK: 0.4182 [0.2776, 0.5466]
-[2025-06-30 23:55:32,845][__main__][INFO] -   Macro_F1: 0.2962 [0.2154, 0.3977]
-[2025-06-30 23:55:32,845][__main__][INFO] -   Weighted_F1: 0.3818 [0.2993, 0.4641]
-[2025-06-30 23:55:32,845][__main__][INFO] - Inference results: {'accuracy': 0.37681159420289856, 'RMSE': 55.32512598464997, 'QWK': 0.4220445459737294, 'HDIV': 0.06521739130434778, 'Macro_F1': 0.2801049472150572, 'Micro_F1': 0.37681159420289856, 'Weighted_F1': 0.38226236003582026, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(13), 'TN_1': np.int64(90), 'FP_1': np.int64(13), 'FN_1': np.int64(22), 'TP_2': np.int64(3), 'TN_2': np.int64(112), 'FP_2': np.int64(21), 'FN_2': np.int64(2), 'TP_3': np.int64(25), 'TN_3': np.int64(56), 'FP_3': np.int64(31), 'FN_3': np.int64(26), 'TP_4': np.int64(5), 'TN_4': np.int64(99), 'FP_4': np.int64(13), 'FN_4': np.int64(21), 'TP_5': np.int64(6), 'TN_5': np.int64(110), 'FP_5': np.int64(8), 'FN_5': np.int64(14)}
-[2025-06-30 23:55:32,845][__main__][INFO] - Inference experiment completed
+[2025-07-10 00:36:24,493][transformers.trainer][INFO] -   Num examples = 138
+[2025-07-10 00:36:24,494][transformers.trainer][INFO] -   Batch size = 16
+[2025-07-10 00:36:25,277][__main__][INFO] - Inference results saved to jbcs2025_bert-base-portuguese-cased-encoder_classification-C3-essay_only-encoder_classification-C3-essay_only_inference_results.jsonl
+[2025-07-10 00:36:25,278][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
+[2025-07-10 00:38:31,831][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
+[2025-07-10 00:38:31,832][__main__][INFO] - Bootstrap Confidence Intervals (95%):
+[2025-07-10 00:38:31,832][__main__][INFO] -   QWK: 0.3469 [0.1991, 0.4852]
+[2025-07-10 00:38:31,832][__main__][INFO] -   Macro_F1: 0.2312 [0.1641, 0.3143]
+[2025-07-10 00:38:31,832][__main__][INFO] -   Weighted_F1: 0.2679 [0.1940, 0.3454]
+[2025-07-10 00:38:31,832][__main__][INFO] - Inference results: {'accuracy': 0.3115942028985507, 'RMSE': 51.07539184552491, 'QWK': 0.3491384731480316, 'HDIV': 0.050724637681159424, 'Macro_F1': 0.21826640792158034, 'Micro_F1': 0.3115942028985507, 'Weighted_F1': 0.26630624081898446, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(107), 'FP_1': np.int64(2), 'FN_1': np.int64(29), 'TP_2': np.int64(14), 'TN_2': np.int64(94), 'FP_2': np.int64(26), 'FN_2': np.int64(4), 'TP_3': np.int64(18), 'TN_3': np.int64(57), 'FP_3': np.int64(36), 'FN_3': np.int64(27), 'TP_4': np.int64(9), 'TN_4': np.int64(81), 'FP_4': np.int64(19), 'FN_4': np.int64(29), 'TP_5': np.int64(2), 'TN_5': np.int64(119), 'FP_5': np.int64(12), 'FN_5': np.int64(5)}
+[2025-07-10 00:38:31,832][__main__][INFO] - Inference experiment completed

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only}/.hydra/config.yaml

@@ -20,12 +20,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C4
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/bertimbau_base/C4
-    logging_dir: ./logs/bertimbau_base/C4
-    best_model_dir: ./results/bertimbau_base/C4/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only}/.hydra/hydra.yaml

@@ -1,6 +1,6 @@
 hydra:
   run:
-    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    dir: inference_output/2025-07-10/00-38-36
   sweep:
     dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
     subdir: ${hydra.job.num}
@@ -110,13 +110,14 @@ hydra:
   output_subdir: .hydra
   overrides:
     hydra:
+    - hydra.run.dir=inference_output/2025-07-10/00-38-36
     - hydra.mode=RUN
     task:
-    - experiments=base_models/C4
+    - experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
   job:
     name: run_inference_experiment
     chdir: null
-    override_dirname: experiments=base_models/C4
+    override_dirname: experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
     id: ???
     num: ???
     config_name: config
@@ -141,9 +142,9 @@ hydra:
     - path: ''
       schema: structured
       provider: schema
-    output_dir: /workspace/jbcs2025/outputs/2025-06-30/23-57-45
+    output_dir: /workspace/jbcs2025/inference_output/2025-07-10/00-38-36
     choices:
-      experiments: base_models/C4
+      experiments: temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
       hydra/env: default
       hydra/callbacks: null
       hydra/job_logging: default

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only/.hydra/overrides.yaml

@@ -0,0 +1 @@
+- experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only}/bootstrap_confidence_intervals.csv

@@ -1,2 +1,2 @@
 experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
-jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only,2025-06-30 23:53:32,0.41819188204779456,0.27759865754644286,0.5466018786751335,0.2690032211286907,0.29623085261327686,0.21542890620802888,0.3976815226515651,0.18225261644353621,0.3817868369579885,0.2993269590182539,0.46412896590642116,0.16480200688816726
+jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only,2025-07-10 00:38:42,0.5435296340232288,0.4184589340416943,0.6551030761025943,0.2366441420609,0.36421051718441505,0.254025794056358,0.5230880773040134,0.2690622832476554,0.5514773744123801,0.46507790634693985,0.6358729541143203,0.17079504776738047

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only}/evaluation_results.csv

@@ -1,2 +1,2 @@
-accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
-0.37681159420289856,52.64042641120627,0.3452054794520547,0.09420289855072461,0.25943499029705924,0.37681159420289856,0.33380294701134283,0,137,0,1,0,109,0,29,13,101,19,5,20,71,22,25,17,67,33,21,2,119,12,5,2025-06-30 23:55:38,jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only
+accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
+0.5362318840579711,31.20757990421976,0.5471167369901547,0.007246376811594235,0.31768171092726494,0.5362318840579711,0.5501656251760338,0,137,0,1,0,137,0,1,7,102,27,2,47,41,21,29,16,84,8,30,4,125,8,1,2025-07-10 00:38:42,jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only}/run_inference_experiment.log

@@ -1,5 +1,5 @@
-[2025-06-30 23:57:45,116][__main__][INFO] - Starting inference experiment
-[2025-06-30 23:57:45,117][__main__][INFO] - cache_dir: /tmp/
+[2025-07-10 00:38:42,200][__main__][INFO] - Starting inference experiment
+[2025-07-10 00:38:42,202][__main__][INFO] - cache_dir: /tmp/
 dataset:
   name: kamel-usp/aes_enem_dataset
   split: JBCS2025
@@ -21,12 +21,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C4
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/bertimbau_base/C4
-    logging_dir: ./logs/bertimbau_base/C4
-    best_model_dir: ./results/bertimbau_base/C4/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:
@@ -41,9 +41,9 @@ experiments:
     gradient_accumulation_steps: 1
     gradient_checkpointing: false
 
-[2025-06-30 23:57:45,119][__main__][INFO] - Running inference with fine-tuned HF model
-[2025-06-30 23:57:50,144][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:57:50,145][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:38:42,204][__main__][INFO] - Running inference with fine-tuned HF model
+[2025-07-10 00:38:47,581][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:38:47,582][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -68,20 +68,14 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:57:50,350][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-06-30 23:57:50,350][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-06-30 23:57:50,350][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-06-30 23:57:50,350][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-06-30 23:57:50,350][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-06-30 23:57:50,350][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-06-30 23:57:50,350][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:57:50,351][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:38:47,831][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:38:47,832][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -106,14 +100,20 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:57:50,376][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-06-30 23:57:50,376][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:38:48,390][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
+[2025-07-10 00:38:48,390][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
+[2025-07-10 00:38:48,390][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
+[2025-07-10 00:38:48,390][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
+[2025-07-10 00:38:48,390][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
+[2025-07-10 00:38:48,390][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
+[2025-07-10 00:38:48,391][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:38:48,391][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -138,18 +138,73 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:57:50,392][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True; Use Full Context: False
-[2025-06-30 23:57:50,599][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C4
-[2025-06-30 23:57:50,599][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C4
-[2025-06-30 23:57:51,501][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
-[2025-06-30 23:57:52,494][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C4/snapshots/be129129fc134c0e782ae9f62b33da331367ab7b/config.json
-[2025-06-30 23:57:52,494][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:38:48,421][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:38:48,421][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 29794
+}
+
+[2025-07-10 00:38:48,438][__main__][INFO] - Tokenizer function parameters- Padding:longest; Truncation: True; Use Full Context: False
+[2025-07-10 00:38:48,876][__main__][INFO] - 
+Token statistics for 'train' split:
+[2025-07-10 00:38:48,876][__main__][INFO] -   Total examples: 500
+[2025-07-10 00:38:48,876][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:38:48,876][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:38:48,876][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:38:48,876][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:38:48,971][__main__][INFO] - 
+Token statistics for 'validation' split:
+[2025-07-10 00:38:48,972][__main__][INFO] -   Total examples: 132
+[2025-07-10 00:38:48,972][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:38:48,972][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:38:48,972][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:38:48,972][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:38:49,072][__main__][INFO] - 
+Token statistics for 'test' split:
+[2025-07-10 00:38:49,072][__main__][INFO] -   Total examples: 138
+[2025-07-10 00:38:49,072][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:38:49,072][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:38:49,072][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:38:49,072][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:38:49,072][__main__][INFO] - If token statistics are the same (max, avg, min) keep in mind that this is due to batched tokenization and padding.
+[2025-07-10 00:38:49,072][__main__][INFO] - Model max length: 512. If it is the same as stats, then there is a high chance that sequences are being truncated.
+[2025-07-10 00:38:49,073][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
+[2025-07-10 00:38:49,073][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only
+[2025-07-10 00:38:50,033][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
+[2025-07-10 00:38:50,973][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only/snapshots/5ed8cb6c9c541d19f43a96b369ea78181d9617f0/config.json
+[2025-07-10 00:38:50,974][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForSequenceClassification"
   ],
@@ -190,37 +245,36 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-06-30 23:58:07,769][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C4/snapshots/be129129fc134c0e782ae9f62b33da331367ab7b/model.safetensors
-[2025-06-30 23:58:07,770][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
-[2025-06-30 23:58:07,770][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-06-30 23:58:08,132][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
+[2025-07-10 00:39:00,410][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only/snapshots/5ed8cb6c9c541d19f43a96b369ea78181d9617f0/model.safetensors
+[2025-07-10 00:39:00,411][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
+[2025-07-10 00:39:00,411][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
+[2025-07-10 00:39:00,802][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
 
-[2025-06-30 23:58:08,133][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bertimbau_base-C4.
+[2025-07-10 00:39:00,803][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only.
 If your task is similar to the task the model of the checkpoint was trained on, you can already use BertForSequenceClassification for predictions without further training.
-[2025-06-30 23:58:08,138][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-06-30 23:58:08,191][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
-[2025-06-30 23:58:08,196][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-06-30 23:58:08,215][transformers.trainer][INFO] - Using auto half precision backend
-[2025-06-30 23:58:11,691][__main__][INFO] - Running inference on test dataset
-[2025-06-30 23:58:11,692][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: reference, essay_text, supporting_text, grades, id_prompt, id, essay_year, prompt. If reference, essay_text, supporting_text, grades, id_prompt, id, essay_year, prompt are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-06-30 23:58:11,696][transformers.trainer][INFO] - 
+[2025-07-10 00:39:00,812][transformers.training_args][INFO] - PyTorch: setting up devices
+[2025-07-10 00:39:00,836][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+[2025-07-10 00:39:00,843][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
+[2025-07-10 00:39:00,871][transformers.trainer][INFO] - Using auto half precision backend
+[2025-07-10 00:39:04,179][__main__][INFO] - Running inference on test dataset
+[2025-07-10 00:39:04,180][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: grades, id, prompt, essay_year, reference, essay_text, supporting_text, id_prompt. If grades, id, prompt, essay_year, reference, essay_text, supporting_text, id_prompt are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
+[2025-07-10 00:39:04,186][transformers.trainer][INFO] - 
 ***** Running Prediction *****
-[2025-06-30 23:58:11,696][transformers.trainer][INFO] -   Num examples = 138
-[2025-06-30 23:58:11,696][transformers.trainer][INFO] -   Batch size = 16
-[2025-06-30 23:58:12,089][__main__][INFO] - Inference results saved to jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only_inference_results.jsonl
-[2025-06-30 23:58:12,096][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
-[2025-06-30 23:59:49,674][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
-[2025-06-30 23:59:49,674][__main__][INFO] - Bootstrap Confidence Intervals (95%):
-[2025-06-30 23:59:49,674][__main__][INFO] -   QWK: 0.6233 [0.5111, 0.7251]
-[2025-06-30 23:59:49,674][__main__][INFO] -   Macro_F1: 0.4137 [0.2906, 0.5906]
-[2025-06-30 23:59:49,674][__main__][INFO] -   Weighted_F1: 0.6557 [0.5749, 0.7321]
-[2025-06-30 23:59:49,674][__main__][INFO] - Inference results: {'accuracy': 0.644927536231884, 'RMSE': 26.37521893583148, 'QWK': 0.6258134490238612, 'HDIV': 0.007246376811594235, 'Macro_F1': 0.36114488348530904, 'Micro_F1': 0.644927536231884, 'Weighted_F1': 0.6545879036165807, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(137), 'FP_1': np.int64(0), 'FN_1': np.int64(1), 'TP_2': np.int64(5), 'TN_2': np.int64(118), 'FP_2': np.int64(11), 'FN_2': np.int64(4), 'TP_3': np.int64(51), 'TN_3': np.int64(49), 'FP_3': np.int64(13), 'FN_3': np.int64(25), 'TP_4': np.int64(30), 'TN_4': np.int64(74), 'FP_4': np.int64(18), 'FN_4': np.int64(16), 'TP_5': np.int64(3), 'TN_5': np.int64(126), 'FP_5': np.int64(7), 'FN_5': np.int64(2)}
-[2025-06-30 23:59:49,675][__main__][INFO] - Inference experiment completed
+[2025-07-10 00:39:04,186][transformers.trainer][INFO] -   Num examples = 138
+[2025-07-10 00:39:04,187][transformers.trainer][INFO] -   Batch size = 16
+[2025-07-10 00:39:05,077][__main__][INFO] - Inference results saved to jbcs2025_bert-base-portuguese-cased-encoder_classification-C4-essay_only-encoder_classification-C4-essay_only_inference_results.jsonl
+[2025-07-10 00:39:05,078][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
+[2025-07-10 00:41:12,570][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
+[2025-07-10 00:41:12,570][__main__][INFO] - Bootstrap Confidence Intervals (95%):
+[2025-07-10 00:41:12,570][__main__][INFO] -   QWK: 0.5435 [0.4185, 0.6551]
+[2025-07-10 00:41:12,570][__main__][INFO] -   Macro_F1: 0.3642 [0.2540, 0.5231]
+[2025-07-10 00:41:12,570][__main__][INFO] -   Weighted_F1: 0.5515 [0.4651, 0.6359]
+[2025-07-10 00:41:12,571][__main__][INFO] - Inference results: {'accuracy': 0.5362318840579711, 'RMSE': 31.20757990421976, 'QWK': 0.5471167369901547, 'HDIV': 0.007246376811594235, 'Macro_F1': 0.31768171092726494, 'Micro_F1': 0.5362318840579711, 'Weighted_F1': 0.5501656251760338, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(137), 'FP_1': np.int64(0), 'FN_1': np.int64(1), 'TP_2': np.int64(7), 'TN_2': np.int64(102), 'FP_2': np.int64(27), 'FN_2': np.int64(2), 'TP_3': np.int64(47), 'TN_3': np.int64(41), 'FP_3': np.int64(21), 'FN_3': np.int64(29), 'TP_4': np.int64(16), 'TN_4': np.int64(84), 'FP_4': np.int64(8), 'FN_4': np.int64(30), 'TP_5': np.int64(4), 'TN_5': np.int64(125), 'FP_5': np.int64(8), 'FN_5': np.int64(1)}
+[2025-07-10 00:41:12,572][__main__][INFO] - Inference experiment completed

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only}/.hydra/config.yaml

@@ -20,12 +20,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C5
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/bertimbau_base/C5
-    logging_dir: ./logs/bertimbau_base/C5
-    best_model_dir: ./results/bertimbau_base/C5/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only/.hydra/hydra.yaml

@@ -0,0 +1,157 @@
+hydra:
+  run:
+    dir: inference_output/2025-07-10/00-41-17
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=inference_output/2025-07-10/00-41-17
+    - hydra.mode=RUN
+    task:
+    - experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
+  job:
+    name: run_inference_experiment
+    chdir: null
+    override_dirname: experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
+    id: ???
+    num: ???
+    config_name: config
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.1'
+    cwd: /workspace/jbcs2025
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /workspace/jbcs2025/configs
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /workspace/jbcs2025/inference_output/2025-07-10/00-41-17
+    choices:
+      experiments: temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only/.hydra/overrides.yaml

@@ -0,0 +1 @@
+- experiments=temp_inference/kamel-usp_jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only

runs/base_models/bertimbau/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only/bootstrap_confidence_intervals.csv

@@ -0,0 +1,2 @@
+experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
+jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only,2025-07-10 00:41:22,0.6257235463885343,0.5090039348253902,0.7265976075113407,0.21759367268595053,0.3040685783009996,0.24405777738239762,0.3809607821665941,0.1369030047841965,0.3590255329781086,0.27462031936437037,0.44809835701310474,0.17347803764873437

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only}/evaluation_results.csv

@@ -1,2 +1,2 @@
-accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
-0.37681159420289856,55.32512598464997,0.4220445459737294,0.06521739130434778,0.2801049472150572,0.37681159420289856,0.38226236003582026,0,137,0,1,13,90,13,22,3,112,21,2,25,56,31,26,5,99,13,21,6,110,8,14,2025-06-30 23:53:32,jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only
+accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
+0.4057971014492754,52.53018455949943,0.629166290308012,0.07246376811594202,0.30402855742671303,0.4057971014492754,0.359115694090939,15,105,11,7,7,85,21,25,5,93,21,19,2,111,2,23,27,79,27,5,0,135,0,3,2025-07-10 00:41:22,jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only

runs/base_models/bertimbau/{jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only → jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only}/run_inference_experiment.log

@@ -1,5 +1,5 @@
-[2025-06-30 23:59:55,461][__main__][INFO] - Starting inference experiment
-[2025-06-30 23:59:55,462][__main__][INFO] - cache_dir: /tmp/
+[2025-07-10 00:41:22,791][__main__][INFO] - Starting inference experiment
+[2025-07-10 00:41:22,793][__main__][INFO] - cache_dir: /tmp/
 dataset:
   name: kamel-usp/aes_enem_dataset
   split: JBCS2025
@@ -21,12 +21,12 @@ post_training_results:
   model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
 experiments:
   model:
-    name: kamel-usp/jbcs2025_bertimbau_base-C5
+    name: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
     type: encoder_classification
     num_labels: 6
-    output_dir: ./results/bertimbau_base/C5
-    logging_dir: ./logs/bertimbau_base/C5
-    best_model_dir: ./results/bertimbau_base/C5/best_model
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
   tokenizer:
     name: neuralmind/bert-base-portuguese-cased
   dataset:
@@ -41,9 +41,9 @@ experiments:
     gradient_accumulation_steps: 1
     gradient_checkpointing: false
 
-[2025-06-30 23:59:55,464][__main__][INFO] - Running inference with fine-tuned HF model
-[2025-07-01 00:00:00,755][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-07-01 00:00:00,756][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:41:22,795][__main__][INFO] - Running inference with fine-tuned HF model
+[2025-07-10 00:41:27,077][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:41:27,079][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -68,20 +68,14 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-07-01 00:00:00,980][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
-[2025-07-01 00:00:00,980][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
-[2025-07-01 00:00:00,980][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
-[2025-07-01 00:00:00,980][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
-[2025-07-01 00:00:00,980][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
-[2025-07-01 00:00:00,980][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
-[2025-07-01 00:00:00,980][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-07-01 00:00:00,981][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:41:27,284][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:41:27,285][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -106,14 +100,20 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-07-01 00:00:01,006][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
-[2025-07-01 00:00:01,007][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:41:27,487][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/vocab.txt
+[2025-07-10 00:41:27,487][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
+[2025-07-10 00:41:27,487][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/added_tokens.json
+[2025-07-10 00:41:27,487][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/special_tokens_map.json
+[2025-07-10 00:41:27,487][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/tokenizer_config.json
+[2025-07-10 00:41:27,487][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
+[2025-07-10 00:41:27,487][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:41:27,488][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForMaskedLM"
   ],
@@ -138,18 +138,73 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-07-01 00:00:01,023][__main__][INFO] - Tokenizer function parameters- Padding:max_length; Truncation: True; Use Full Context: False
-[2025-07-01 00:00:01,223][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C5
-[2025-07-01 00:00:01,223][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bertimbau_base-C5
-[2025-07-01 00:00:02,086][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
-[2025-07-01 00:00:02,975][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C5/snapshots/fb36ac8b730b27c491174f81a69d6da1c0962026/config.json
-[2025-07-01 00:00:02,976][transformers.configuration_utils][INFO] - Model config BertConfig {
+[2025-07-10 00:41:27,520][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--neuralmind--bert-base-portuguese-cased/snapshots/94d69c95f98f7d5b2a8700c420230ae10def0baa/config.json
+[2025-07-10 00:41:27,520][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 29794
+}
+
+[2025-07-10 00:41:27,539][__main__][INFO] - Tokenizer function parameters- Padding:longest; Truncation: True; Use Full Context: False
+[2025-07-10 00:41:27,963][__main__][INFO] - 
+Token statistics for 'train' split:
+[2025-07-10 00:41:27,964][__main__][INFO] -   Total examples: 500
+[2025-07-10 00:41:27,964][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:41:27,964][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:41:27,964][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:41:27,964][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:41:28,061][__main__][INFO] - 
+Token statistics for 'validation' split:
+[2025-07-10 00:41:28,061][__main__][INFO] -   Total examples: 132
+[2025-07-10 00:41:28,062][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:41:28,062][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:41:28,062][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:41:28,062][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:41:28,162][__main__][INFO] - 
+Token statistics for 'test' split:
+[2025-07-10 00:41:28,162][__main__][INFO] -   Total examples: 138
+[2025-07-10 00:41:28,162][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:41:28,162][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:41:28,162][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:41:28,162][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:41:28,162][__main__][INFO] - If token statistics are the same (max, avg, min) keep in mind that this is due to batched tokenization and padding.
+[2025-07-10 00:41:28,162][__main__][INFO] - Model max length: 512. If it is the same as stats, then there is a high chance that sequences are being truncated.
+[2025-07-10 00:41:28,163][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
+[2025-07-10 00:41:28,163][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only
+[2025-07-10 00:41:29,268][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.58 for training 
+[2025-07-10 00:41:30,165][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only/snapshots/15a44128caf634f8d6327daaa8b803cd4b8339f8/config.json
+[2025-07-10 00:41:30,165][transformers.configuration_utils][INFO] - Model config BertConfig {
   "architectures": [
     "BertForSequenceClassification"
   ],
@@ -190,37 +245,36 @@ experiments:
   "pooler_size_per_head": 128,
   "pooler_type": "first_token_transform",
   "position_embedding_type": "absolute",
-  "problem_type": "single_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.53.0",
+  "transformers_version": "4.53.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 29794
 }
 
-[2025-07-01 00:00:15,970][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bertimbau_base-C5/snapshots/fb36ac8b730b27c491174f81a69d6da1c0962026/model.safetensors
-[2025-07-01 00:00:15,970][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
-[2025-07-01 00:00:15,971][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
-[2025-07-01 00:00:16,336][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
+[2025-07-10 00:41:38,557][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only/snapshots/15a44128caf634f8d6327daaa8b803cd4b8339f8/model.safetensors
+[2025-07-10 00:41:38,559][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
+[2025-07-10 00:41:38,559][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
+[2025-07-10 00:41:38,941][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
 
-[2025-07-01 00:00:16,336][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bertimbau_base-C5.
+[2025-07-10 00:41:38,942][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only.
 If your task is similar to the task the model of the checkpoint was trained on, you can already use BertForSequenceClassification for predictions without further training.
-[2025-07-01 00:00:16,341][transformers.training_args][INFO] - PyTorch: setting up devices
-[2025-07-01 00:00:16,396][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
-[2025-07-01 00:00:16,401][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
-[2025-07-01 00:00:16,420][transformers.trainer][INFO] - Using auto half precision backend
-[2025-07-01 00:00:19,893][__main__][INFO] - Running inference on test dataset
-[2025-07-01 00:00:19,894][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: supporting_text, grades, essay_text, id_prompt, prompt, essay_year, reference, id. If supporting_text, grades, essay_text, id_prompt, prompt, essay_year, reference, id are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
-[2025-07-01 00:00:19,898][transformers.trainer][INFO] - 
+[2025-07-10 00:41:38,951][transformers.training_args][INFO] - PyTorch: setting up devices
+[2025-07-10 00:41:38,976][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+[2025-07-10 00:41:38,985][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
+[2025-07-10 00:41:39,013][transformers.trainer][INFO] - Using auto half precision backend
+[2025-07-10 00:41:42,342][__main__][INFO] - Running inference on test dataset
+[2025-07-10 00:41:42,344][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: id, id_prompt, supporting_text, grades, essay_text, prompt, reference, essay_year. If id, id_prompt, supporting_text, grades, essay_text, prompt, reference, essay_year are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
+[2025-07-10 00:41:42,350][transformers.trainer][INFO] - 
 ***** Running Prediction *****
-[2025-07-01 00:00:19,898][transformers.trainer][INFO] -   Num examples = 138
-[2025-07-01 00:00:19,898][transformers.trainer][INFO] -   Batch size = 16
-[2025-07-01 00:00:20,325][__main__][INFO] - Inference results saved to jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only_inference_results.jsonl
-[2025-07-01 00:00:20,331][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
-[2025-07-01 00:01:56,543][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
-[2025-07-01 00:01:56,543][__main__][INFO] - Bootstrap Confidence Intervals (95%):
-[2025-07-01 00:01:56,543][__main__][INFO] -   QWK: 0.4735 [0.3402, 0.5948]
-[2025-07-01 00:01:56,543][__main__][INFO] -   Macro_F1: 0.2047 [0.1470, 0.2727]
-[2025-07-01 00:01:56,543][__main__][INFO] -   Weighted_F1: 0.2575 [0.1803, 0.3395]
-[2025-07-01 00:01:56,543][__main__][INFO] - Inference results: {'accuracy': 0.3188405797101449, 'RMSE': 61.2904702146299, 'QWK': 0.476219483623073, 'HDIV': 0.13043478260869568, 'Macro_F1': 0.2055897809038726, 'Micro_F1': 0.3188405797101449, 'Weighted_F1': 0.25808413038205613, 'TP_0': np.int64(3), 'TN_0': np.int64(113), 'FP_0': np.int64(3), 'FN_0': np.int64(19), 'TP_1': np.int64(9), 'TN_1': np.int64(71), 'FP_1': np.int64(35), 'FN_1': np.int64(23), 'TP_2': np.int64(3), 'TN_2': np.int64(103), 'FP_2': np.int64(11), 'FN_2': np.int64(21), 'TP_3': np.int64(1), 'TN_3': np.int64(108), 'FP_3': np.int64(5), 'FN_3': np.int64(24), 'TP_4': np.int64(28), 'TN_4': np.int64(66), 'FP_4': np.int64(40), 'FN_4': np.int64(4), 'TP_5': np.int64(0), 'TN_5': np.int64(135), 'FP_5': np.int64(0), 'FN_5': np.int64(3)}
-[2025-07-01 00:01:56,543][__main__][INFO] - Inference experiment completed
+[2025-07-10 00:41:42,350][transformers.trainer][INFO] -   Num examples = 138
+[2025-07-10 00:41:42,350][transformers.trainer][INFO] -   Batch size = 16
+[2025-07-10 00:41:43,340][__main__][INFO] - Inference results saved to jbcs2025_bert-base-portuguese-cased-encoder_classification-C5-essay_only-encoder_classification-C5-essay_only_inference_results.jsonl
+[2025-07-10 00:41:43,341][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
+[2025-07-10 00:43:47,972][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
+[2025-07-10 00:43:47,972][__main__][INFO] - Bootstrap Confidence Intervals (95%):
+[2025-07-10 00:43:47,972][__main__][INFO] -   QWK: 0.6257 [0.5090, 0.7266]
+[2025-07-10 00:43:47,972][__main__][INFO] -   Macro_F1: 0.3041 [0.2441, 0.3810]
+[2025-07-10 00:43:47,972][__main__][INFO] -   Weighted_F1: 0.3590 [0.2746, 0.4481]
+[2025-07-10 00:43:47,972][__main__][INFO] - Inference results: {'accuracy': 0.4057971014492754, 'RMSE': 52.53018455949943, 'QWK': 0.629166290308012, 'HDIV': 0.07246376811594202, 'Macro_F1': 0.30402855742671303, 'Micro_F1': 0.4057971014492754, 'Weighted_F1': 0.359115694090939, 'TP_0': np.int64(15), 'TN_0': np.int64(105), 'FP_0': np.int64(11), 'FN_0': np.int64(7), 'TP_1': np.int64(7), 'TN_1': np.int64(85), 'FP_1': np.int64(21), 'FN_1': np.int64(25), 'TP_2': np.int64(5), 'TN_2': np.int64(93), 'FP_2': np.int64(21), 'FN_2': np.int64(19), 'TP_3': np.int64(2), 'TN_3': np.int64(111), 'FP_3': np.int64(2), 'FN_3': np.int64(23), 'TP_4': np.int64(27), 'TN_4': np.int64(79), 'FP_4': np.int64(27), 'FN_4': np.int64(5), 'TP_5': np.int64(0), 'TN_5': np.int64(135), 'FP_5': np.int64(0), 'FN_5': np.int64(3)}
+[2025-07-10 00:43:47,972][__main__][INFO] - Inference experiment completed

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only/.hydra/overrides.yaml

@@ -1 +0,0 @@
-- experiments=base_models/C1

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only/.hydra/overrides.yaml

@@ -1 +0,0 @@
-- experiments=base_models/C2

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only/.hydra/overrides.yaml

@@ -1 +0,0 @@
-- experiments=base_models/C3

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only/.hydra/overrides.yaml

@@ -1 +0,0 @@
-- experiments=base_models/C4

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only/.hydra/hydra.yaml

@@ -1,156 +0,0 @@
-hydra:
-  run:
-    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
-  sweep:
-    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
-    subdir: ${hydra.job.num}
-  launcher:
-    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
-  sweeper:
-    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
-    max_batch_size: null
-    params: null
-  help:
-    app_name: ${hydra.job.name}
-    header: '${hydra.help.app_name} is powered by Hydra.
-
-      '
-    footer: 'Powered by Hydra (https://hydra.cc)
-
-      Use --hydra-help to view Hydra specific help
-
-      '
-    template: '${hydra.help.header}
-
-      == Configuration groups ==
-
-      Compose your configuration from those groups (group=option)
-
-
-      $APP_CONFIG_GROUPS
-
-
-      == Config ==
-
-      Override anything in the config (foo.bar=value)
-
-
-      $CONFIG
-
-
-      ${hydra.help.footer}
-
-      '
-  hydra_help:
-    template: 'Hydra (${hydra.runtime.version})
-
-      See https://hydra.cc for more info.
-
-
-      == Flags ==
-
-      $FLAGS_HELP
-
-
-      == Configuration groups ==
-
-      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
-      to command line)
-
-
-      $HYDRA_CONFIG_GROUPS
-
-
-      Use ''--cfg hydra'' to Show the Hydra config.
-
-      '
-    hydra_help: ???
-  hydra_logging:
-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][HYDRA] %(message)s'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: simple
-        stream: ext://sys.stdout
-    root:
-      level: INFO
-      handlers:
-      - console
-    loggers:
-      logging_example:
-        level: DEBUG
-    disable_existing_loggers: false
-  job_logging:
-    version: 1
-    formatters:
-      simple:
-        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
-    handlers:
-      console:
-        class: logging.StreamHandler
-        formatter: simple
-        stream: ext://sys.stdout
-      file:
-        class: logging.FileHandler
-        formatter: simple
-        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
-    root:
-      level: INFO
-      handlers:
-      - console
-      - file
-    disable_existing_loggers: false
-  env: {}
-  mode: RUN
-  searchpath: []
-  callbacks: {}
-  output_subdir: .hydra
-  overrides:
-    hydra:
-    - hydra.mode=RUN
-    task:
-    - experiments=base_models/C5
-  job:
-    name: run_inference_experiment
-    chdir: null
-    override_dirname: experiments=base_models/C5
-    id: ???
-    num: ???
-    config_name: config
-    env_set: {}
-    env_copy: []
-    config:
-      override_dirname:
-        kv_sep: '='
-        item_sep: ','
-        exclude_keys: []
-  runtime:
-    version: 1.3.2
-    version_base: '1.1'
-    cwd: /workspace/jbcs2025
-    config_sources:
-    - path: hydra.conf
-      schema: pkg
-      provider: hydra
-    - path: /workspace/jbcs2025/configs
-      schema: file
-      provider: main
-    - path: ''
-      schema: structured
-      provider: schema
-    output_dir: /workspace/jbcs2025/outputs/2025-06-30/23-59-55
-    choices:
-      experiments: base_models/C5
-      hydra/env: default
-      hydra/callbacks: null
-      hydra/job_logging: default
-      hydra/hydra_logging: default
-      hydra/hydra_help: default
-      hydra/help: default
-      hydra/sweeper: basic
-      hydra/launcher: basic
-      hydra/output: default
-  verbose: false

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only/.hydra/overrides.yaml

@@ -1 +0,0 @@
-- experiments=base_models/C5

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only/bootstrap_confidence_intervals.csv

@@ -1,2 +0,0 @@
-experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
-jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only,2025-06-30 23:59:55,0.47349799901126716,0.3401973117894254,0.5947975929869902,0.2546002811975648,0.20469588256838514,0.14697576658446224,0.27274642041824704,0.1257706538337848,0.25750931482031114,0.18034272476682853,0.33952288243091566,0.15918015766408714

runs/base_models/bertimbau/jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only/evaluation_results.csv

@@ -1,2 +0,0 @@
-accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
-0.3188405797101449,61.2904702146299,0.476219483623073,0.13043478260869568,0.2055897809038726,0.3188405797101449,0.25808413038205613,3,113,3,19,9,71,35,23,3,103,11,21,1,108,5,24,28,66,40,4,0,135,0,3,2025-06-30 23:59:55,jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only

runs/base_models/bertugues/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/.hydra/config.yaml

@@ -0,0 +1,41 @@
+cache_dir: /tmp/
+dataset:
+  name: kamel-usp/aes_enem_dataset
+  split: JBCS2025
+training_params:
+  seed: 42
+  num_train_epochs: 20
+  logging_steps: 100
+  metric_for_best_model: QWK
+  bf16: true
+bootstrap:
+  enabled: true
+  n_bootstrap: 10000
+  bootstrap_seed: 42
+  metrics:
+  - QWK
+  - Macro_F1
+  - Weighted_F1
+post_training_results:
+  model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
+experiments:
+  model:
+    name: kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+    type: encoder_classification
+    num_labels: 6
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+  tokenizer:
+    name: ricardoz/BERTugues-base-portuguese-cased
+  dataset:
+    grade_index: 0
+    use_full_context: false
+  training_params:
+    weight_decay: 0.01
+    warmup_ratio: 0.1
+    learning_rate: 5.0e-05
+    train_batch_size: 16
+    eval_batch_size: 16
+    gradient_accumulation_steps: 1
+    gradient_checkpointing: false

runs/base_models/bertugues/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/.hydra/hydra.yaml

@@ -0,0 +1,157 @@
+hydra:
+  run:
+    dir: inference_output/2025-07-10/00-57-36
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=inference_output/2025-07-10/00-57-36
+    - hydra.mode=RUN
+    task:
+    - experiments=temp_inference/kamel-usp_jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+  job:
+    name: run_inference_experiment
+    chdir: null
+    override_dirname: experiments=temp_inference/kamel-usp_jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+    id: ???
+    num: ???
+    config_name: config
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.1'
+    cwd: /workspace/jbcs2025
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /workspace/jbcs2025/configs
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /workspace/jbcs2025/inference_output/2025-07-10/00-57-36
+    choices:
+      experiments: temp_inference/kamel-usp_jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

runs/base_models/bertugues/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/.hydra/overrides.yaml

@@ -0,0 +1 @@
+- experiments=temp_inference/kamel-usp_jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only

runs/base_models/bertugues/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/bootstrap_confidence_intervals.csv

@@ -0,0 +1,2 @@
+experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
+jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only,2025-07-10 00:57:41,0.6118239365325281,0.5155564145265364,0.7026110342235472,0.18705461969701076,0.41828021220630307,0.3165853797061227,0.5526803717911853,0.23609499208506263,0.5627013765718267,0.4791976087167935,0.6438201797903147,0.16462257107352118

runs/base_models/bertugues/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/evaluation_results.csv

@@ -0,0 +1,2 @@
+accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
+0.5434782608695652,30.45547950507524,0.6139860139860139,0.007246376811594235,0.38733766233766237,0.5434782608695652,0.5620203065855239,0,137,0,1,0,138,0,0,7,109,19,3,35,61,11,31,28,67,20,23,5,115,13,5,2025-07-10 00:57:41,jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only

runs/base_models/bertugues/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only/run_inference_experiment.log

@@ -0,0 +1,250 @@
+[2025-07-10 00:57:41,959][__main__][INFO] - Starting inference experiment
+[2025-07-10 00:57:41,961][__main__][INFO] - cache_dir: /tmp/
+dataset:
+  name: kamel-usp/aes_enem_dataset
+  split: JBCS2025
+training_params:
+  seed: 42
+  num_train_epochs: 20
+  logging_steps: 100
+  metric_for_best_model: QWK
+  bf16: true
+bootstrap:
+  enabled: true
+  n_bootstrap: 10000
+  bootstrap_seed: 42
+  metrics:
+  - QWK
+  - Macro_F1
+  - Weighted_F1
+post_training_results:
+  model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
+experiments:
+  model:
+    name: kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+    type: encoder_classification
+    num_labels: 6
+    output_dir: ./results/
+    logging_dir: ./logs/
+    best_model_dir: kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+  tokenizer:
+    name: ricardoz/BERTugues-base-portuguese-cased
+  dataset:
+    grade_index: 0
+    use_full_context: false
+  training_params:
+    weight_decay: 0.01
+    warmup_ratio: 0.1
+    learning_rate: 5.0e-05
+    train_batch_size: 16
+    eval_batch_size: 16
+    gradient_accumulation_steps: 1
+    gradient_checkpointing: false
+
+[2025-07-10 00:57:41,963][__main__][INFO] - Running inference with fine-tuned HF model
+[2025-07-10 00:57:47,898][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--ricardoz--BERTugues-base-portuguese-cased/snapshots/76022866e209716d673e144cc9186f7b20830967/config.json
+[2025-07-10 00:57:47,899][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForPreTraining"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}
+
+[2025-07-10 00:57:48,108][transformers.models.auto.tokenization_auto][INFO] - Could not locate the tokenizer configuration file, will try to use the model config instead.
+[2025-07-10 00:57:48,331][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--ricardoz--BERTugues-base-portuguese-cased/snapshots/76022866e209716d673e144cc9186f7b20830967/config.json
+[2025-07-10 00:57:48,332][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForPreTraining"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}
+
+[2025-07-10 00:57:48,944][transformers.tokenization_utils_base][INFO] - loading file vocab.txt from cache at /tmp/models--ricardoz--BERTugues-base-portuguese-cased/snapshots/76022866e209716d673e144cc9186f7b20830967/vocab.txt
+[2025-07-10 00:57:48,944][transformers.tokenization_utils_base][INFO] - loading file tokenizer.json from cache at None
+[2025-07-10 00:57:48,944][transformers.tokenization_utils_base][INFO] - loading file added_tokens.json from cache at None
+[2025-07-10 00:57:48,944][transformers.tokenization_utils_base][INFO] - loading file special_tokens_map.json from cache at None
+[2025-07-10 00:57:48,944][transformers.tokenization_utils_base][INFO] - loading file tokenizer_config.json from cache at None
+[2025-07-10 00:57:48,944][transformers.tokenization_utils_base][INFO] - loading file chat_template.jinja from cache at None
+[2025-07-10 00:57:48,944][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--ricardoz--BERTugues-base-portuguese-cased/snapshots/76022866e209716d673e144cc9186f7b20830967/config.json
+[2025-07-10 00:57:48,945][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForPreTraining"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}
+
+[2025-07-10 00:57:48,977][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--ricardoz--BERTugues-base-portuguese-cased/snapshots/76022866e209716d673e144cc9186f7b20830967/config.json
+[2025-07-10 00:57:48,978][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForPreTraining"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}
+
+[2025-07-10 00:57:48,996][__main__][INFO] - Tokenizer function parameters- Padding:longest; Truncation: True; Use Full Context: False
+[2025-07-10 00:57:49,407][__main__][INFO] - 
+Token statistics for 'train' split:
+[2025-07-10 00:57:49,407][__main__][INFO] -   Total examples: 500
+[2025-07-10 00:57:49,407][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:57:49,407][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:57:49,407][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:57:49,407][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:57:49,497][__main__][INFO] - 
+Token statistics for 'validation' split:
+[2025-07-10 00:57:49,497][__main__][INFO] -   Total examples: 132
+[2025-07-10 00:57:49,497][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:57:49,497][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:57:49,497][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:57:49,497][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:57:49,593][__main__][INFO] - 
+Token statistics for 'test' split:
+[2025-07-10 00:57:49,593][__main__][INFO] -   Total examples: 138
+[2025-07-10 00:57:49,593][__main__][INFO] -   Min tokens: 512
+[2025-07-10 00:57:49,593][__main__][INFO] -   Max tokens: 512
+[2025-07-10 00:57:49,593][__main__][INFO] -   Avg tokens: 512.00
+[2025-07-10 00:57:49,593][__main__][INFO] -   Std tokens: 0.00
+[2025-07-10 00:57:49,593][__main__][INFO] - If token statistics are the same (max, avg, min) keep in mind that this is due to batched tokenization and padding.
+[2025-07-10 00:57:49,593][__main__][INFO] - Model max length: 512. If it is the same as stats, then there is a high chance that sequences are being truncated.
+[2025-07-10 00:57:49,593][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+[2025-07-10 00:57:49,593][__main__][INFO] - Loading model from: kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only
+[2025-07-10 00:57:50,956][__main__][INFO] - Model need ≈ 1.36 GiB to run inference and 2.59 for training 
+[2025-07-10 00:57:51,848][transformers.configuration_utils][INFO] - loading configuration file config.json from cache at /tmp/models--kamel-usp--jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only/snapshots/c8b174c3e6521d94d4c8700c5ae1a12ea8a389b1/config.json
+[2025-07-10 00:57:51,849][transformers.configuration_utils][INFO] - Model config BertConfig {
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": 0,
+    "1": 40,
+    "2": 80,
+    "3": 120,
+    "4": 160,
+    "5": 200
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0": 0,
+    "40": 1,
+    "80": 2,
+    "120": 3,
+    "160": 4,
+    "200": 5
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}
+
+[2025-07-10 00:58:00,510][transformers.modeling_utils][INFO] - loading weights file model.safetensors from cache at /tmp/models--kamel-usp--jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only/snapshots/c8b174c3e6521d94d4c8700c5ae1a12ea8a389b1/model.safetensors
+[2025-07-10 00:58:00,511][transformers.modeling_utils][INFO] - Will use torch_dtype=torch.float32 as defined in model's config object
+[2025-07-10 00:58:00,511][transformers.modeling_utils][INFO] - Instantiating BertForSequenceClassification model under default dtype torch.float32.
+[2025-07-10 00:58:00,897][transformers.modeling_utils][INFO] - All model checkpoint weights were used when initializing BertForSequenceClassification.
+
+[2025-07-10 00:58:00,897][transformers.modeling_utils][INFO] - All the weights of BertForSequenceClassification were initialized from the model checkpoint at kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only.
+If your task is similar to the task the model of the checkpoint was trained on, you can already use BertForSequenceClassification for predictions without further training.
+[2025-07-10 00:58:00,906][transformers.training_args][INFO] - PyTorch: setting up devices
+[2025-07-10 00:58:00,930][transformers.training_args][INFO] - The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
+[2025-07-10 00:58:00,937][transformers.trainer][INFO] - You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set to `True` to avoid any unexpected behavior such as device placement mismatching.
+[2025-07-10 00:58:00,963][transformers.trainer][INFO] - Using auto half precision backend
+[2025-07-10 00:58:04,297][__main__][INFO] - Running inference on test dataset
+[2025-07-10 00:58:04,298][transformers.trainer][INFO] - The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: supporting_text, grades, prompt, id_prompt, id, essay_year, essay_text, reference. If supporting_text, grades, prompt, id_prompt, id, essay_year, essay_text, reference are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
+[2025-07-10 00:58:04,307][transformers.trainer][INFO] - 
+***** Running Prediction *****
+[2025-07-10 00:58:04,307][transformers.trainer][INFO] -   Num examples = 138
+[2025-07-10 00:58:04,307][transformers.trainer][INFO] -   Batch size = 16
+[2025-07-10 00:58:05,176][__main__][INFO] - Inference results saved to jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only-encoder_classification-C1-essay_only_inference_results.jsonl
+[2025-07-10 00:58:05,177][__main__][INFO] - Computing bootstrap confidence intervals for metrics: ['QWK', 'Macro_F1', 'Weighted_F1']
+[2025-07-10 01:00:09,857][__main__][INFO] - Bootstrap CI results saved to bootstrap_confidence_intervals.csv
+[2025-07-10 01:00:09,857][__main__][INFO] - Bootstrap Confidence Intervals (95%):
+[2025-07-10 01:00:09,857][__main__][INFO] -   QWK: 0.6118 [0.5156, 0.7026]
+[2025-07-10 01:00:09,857][__main__][INFO] -   Macro_F1: 0.4183 [0.3166, 0.5527]
+[2025-07-10 01:00:09,857][__main__][INFO] -   Weighted_F1: 0.5627 [0.4792, 0.6438]
+[2025-07-10 01:00:09,857][__main__][INFO] - Inference results: {'accuracy': 0.5434782608695652, 'RMSE': 30.45547950507524, 'QWK': 0.6139860139860139, 'HDIV': 0.007246376811594235, 'Macro_F1': 0.38733766233766237, 'Micro_F1': 0.5434782608695652, 'Weighted_F1': 0.5620203065855239, 'TP_0': np.int64(0), 'TN_0': np.int64(137), 'FP_0': np.int64(0), 'FN_0': np.int64(1), 'TP_1': np.int64(0), 'TN_1': np.int64(138), 'FP_1': np.int64(0), 'FN_1': np.int64(0), 'TP_2': np.int64(7), 'TN_2': np.int64(109), 'FP_2': np.int64(19), 'FN_2': np.int64(3), 'TP_3': np.int64(35), 'TN_3': np.int64(61), 'FP_3': np.int64(11), 'FN_3': np.int64(31), 'TP_4': np.int64(28), 'TN_4': np.int64(67), 'FP_4': np.int64(20), 'FN_4': np.int64(23), 'TP_5': np.int64(5), 'TN_5': np.int64(115), 'FP_5': np.int64(13), 'FN_5': np.int64(5)}
+[2025-07-10 01:00:09,858][__main__][INFO] - Inference experiment completed