audgns

README.md

@@ -3,9 +3,9 @@ library_name: transformers
 license: apache-2.0
 base_model: beomi/kcbert-base
 tags:
-- LMH
+- Lee
 - 10_class
-- multi_labels
+- text-classification
 - generated_from_trainer
 model-index:
 - name: model_output
@@ -17,10 +17,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # model_output
 
-This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the unsmile_data dataset.
+This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) on the unsmile dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1302
-- Lrap: 0.8800
+- Loss: 0.1409
+- Lrap: 0.8762
 
 ## Model description
 
@@ -43,7 +43,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 64
 - eval_batch_size: 64
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 5
 
@@ -51,16 +51,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Lrap   |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| No log        | 1.0   | 235  | 0.1502          | 0.8535 |
-| No log        | 2.0   | 470  | 0.1297          | 0.8706 |
-| 0.1747        | 3.0   | 705  | 0.1229          | 0.8803 |
-| 0.1747        | 4.0   | 940  | 0.1288          | 0.8802 |
-| 0.0784        | 5.0   | 1175 | 0.1302          | 0.8800 |
+| No log        | 1.0   | 235  | 0.1232          | 0.8799 |
+| No log        | 2.0   | 470  | 0.1269          | 0.8759 |
+| 0.1044        | 3.0   | 705  | 0.1300          | 0.8794 |
+| 0.1044        | 4.0   | 940  | 0.1372          | 0.8786 |
+| 0.0523        | 5.0   | 1175 | 0.1409          | 0.8762 |
 
 
 ### Framework versions
 
-- Transformers 4.44.2
-- Pytorch 2.4.1+cu121
-- Datasets 3.0.1
-- Tokenizers 0.19.1
+- Transformers 4.48.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

@@ -49,7 +49,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "multi_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.44.2",
+  "transformers_version": "4.48.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30000

model.safetensors

@@ -1,3 +1,3 @@
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-oid sha256:6d13c298ecbbcee7f77ab97006fe47d017478bcad1d7bc50e1da168a700b1340
+oid sha256:b980a083b5ee363d9e74dd41d3d1e5629f6ad848fa533d7c2dbb05cf03323c4c
 size 435728400

runs/Feb11_05-34-19_293c2c413125/events.out.tfevents.1739252069.293c2c413125.180.0

@@ -0,0 +1,3 @@
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+size 19518

tokenizer_config.json

@@ -45,6 +45,7 @@
   "cls_token": "[CLS]",
   "do_basic_tokenize": true,
   "do_lower_case": false,
+  "extra_special_tokens": {},
   "mask_token": "[MASK]",
   "model_max_length": 300,
   "never_split": null,

training_args.bin

@@ -1,3 +1,3 @@
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-size 5176
+oid sha256:b7968dc82ce0f3dae1106a1193af0faaf227d1616ff198c0a7111732608ed8a8
+size 5368