End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,78 @@
+---
+license: mit
+base_model: FacebookAI/xlm-roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: xlm-roberta-base_lr5e-06_seed42_basic_original_amh-hau-eng_train
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# xlm-roberta-base_lr5e-06_seed42_basic_original_amh-hau-eng_train
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0289
+- Spearman Corr: 0.7801
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-06
+- train_batch_size: 32
+- eval_batch_size: 128
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
+|:-------------:|:-----:|:----:|:---------------:|:-------------:|
+| No log        | 1.55  | 200  | 0.0251          | 0.7275        |
+| 0.0824        | 3.1   | 400  | 0.0250          | 0.7584        |
+| 0.0309        | 4.65  | 600  | 0.0251          | 0.7713        |
+| 0.0251        | 6.2   | 800  | 0.0254          | 0.7824        |
+| 0.0251        | 7.75  | 1000 | 0.0271          | 0.7791        |
+| 0.0222        | 9.3   | 1200 | 0.0258          | 0.7837        |
+| 0.0199        | 10.85 | 1400 | 0.0302          | 0.7791        |
+| 0.0182        | 12.4  | 1600 | 0.0244          | 0.7815        |
+| 0.0166        | 13.95 | 1800 | 0.0299          | 0.7793        |
+| 0.0166        | 15.5  | 2000 | 0.0256          | 0.7818        |
+| 0.0154        | 17.05 | 2200 | 0.0275          | 0.7880        |
+| 0.0145        | 18.6  | 2400 | 0.0283          | 0.7780        |
+| 0.0138        | 20.16 | 2600 | 0.0299          | 0.7810        |
+| 0.0138        | 21.71 | 2800 | 0.0298          | 0.7834        |
+| 0.013         | 23.26 | 3000 | 0.0279          | 0.7813        |
+| 0.0125        | 24.81 | 3200 | 0.0279          | 0.7802        |
+| 0.0119        | 26.36 | 3400 | 0.0281          | 0.7790        |
+| 0.0117        | 27.91 | 3600 | 0.0289          | 0.7801        |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "FacebookAI/xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "XLMRobertaTokenizer",
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+}

training_args.bin

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