End of training

.gitattributes

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 *.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

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+---
+license: mit
+base_model: FacebookAI/xlm-roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: xlm-roberta-base_pan_loss_2e-05
+  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_pan_loss_2e-05
+
+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: 0.0216
+- Spearman Corr: 0.7776
+
+## 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: 2e-05
+- 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        | 0.85  | 200  | 0.0210          | 0.7733        |
+| No log        | 1.69  | 400  | 0.0215          | 0.7798        |
+| 0.0009        | 2.54  | 600  | 0.0219          | 0.7770        |
+| 0.0009        | 3.38  | 800  | 0.0212          | 0.7807        |
+| 0.0006        | 4.23  | 1000 | 0.0224          | 0.7806        |
+| 0.0006        | 5.07  | 1200 | 0.0210          | 0.7800        |
+| 0.0006        | 5.92  | 1400 | 0.0208          | 0.7799        |
+| 0.0004        | 6.77  | 1600 | 0.0214          | 0.7793        |
+| 0.0004        | 7.61  | 1800 | 0.0216          | 0.7795        |
+| 0.0003        | 8.46  | 2000 | 0.0207          | 0.7819        |
+| 0.0003        | 9.3   | 2200 | 0.0209          | 0.7826        |
+| 0.0004        | 10.15 | 2400 | 0.0209          | 0.7793        |
+| 0.0004        | 10.99 | 2600 | 0.0207          | 0.7804        |
+| 0.0004        | 11.84 | 2800 | 0.0210          | 0.7808        |
+| 0.0004        | 12.68 | 3000 | 0.0216          | 0.7776        |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+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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+}

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