Initial Commit

README.md

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+---
+license: mit
+base_model: facebook/xlm-v-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta
+  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. -->
+
+# scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta
+
+This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0448
+- Accuracy: 0.4838
+- F1: 0.4798
+
+## 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-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 11213
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.09  | 250  | 1.0988          | 0.3333   | 0.1667 |
+| 1.0959        | 2.17  | 500  | 1.0989          | 0.3333   | 0.1667 |
+| 1.0959        | 3.26  | 750  | 1.1000          | 0.3333   | 0.1667 |
+| 1.0996        | 4.35  | 1000 | 1.1023          | 0.3333   | 0.1667 |
+| 1.0996        | 5.43  | 1250 | 1.0990          | 0.3333   | 0.1667 |
+| 1.1001        | 6.52  | 1500 | 1.0997          | 0.3333   | 0.1667 |
+| 1.1001        | 7.61  | 1750 | 1.0998          | 0.3333   | 0.1667 |
+| 1.0992        | 8.7   | 2000 | 1.0988          | 0.3333   | 0.1667 |
+| 1.0992        | 9.78  | 2250 | 1.0990          | 0.3333   | 0.1667 |
+| 1.0998        | 10.87 | 2500 | 1.0992          | 0.3333   | 0.1667 |
+| 1.0998        | 11.96 | 2750 | 1.0996          | 0.3333   | 0.1667 |
+| 1.0994        | 13.04 | 3000 | 1.0987          | 0.3333   | 0.1667 |
+| 1.0994        | 14.13 | 3250 | 1.0988          | 0.3333   | 0.1667 |
+| 1.0993        | 15.22 | 3500 | 1.0993          | 0.3333   | 0.1667 |
+| 1.0993        | 16.3  | 3750 | 1.0987          | 0.3333   | 0.1667 |
+| 1.0995        | 17.39 | 4000 | 1.0986          | 0.3333   | 0.1667 |
+| 1.0995        | 18.48 | 4250 | 1.0989          | 0.3333   | 0.1667 |
+| 1.0991        | 19.57 | 4500 | 1.0989          | 0.3333   | 0.1667 |
+| 1.0991        | 20.65 | 4750 | 1.0987          | 0.3333   | 0.1667 |
+| 1.0994        | 21.74 | 5000 | 1.0987          | 0.3333   | 0.1667 |
+| 1.0994        | 22.83 | 5250 | 1.0987          | 0.3333   | 0.1667 |
+| 1.0991        | 23.91 | 5500 | 1.0987          | 0.3333   | 0.1667 |
+| 1.0991        | 25.0  | 5750 | 1.0986          | 0.3333   | 0.1667 |
+| 1.0991        | 26.09 | 6000 | 1.0987          | 0.3333   | 0.1667 |
+| 1.0991        | 27.17 | 6250 | 1.0986          | 0.3333   | 0.1667 |
+| 1.0946        | 28.26 | 6500 | 1.0796          | 0.4560   | 0.4220 |
+| 1.0946        | 29.35 | 6750 | 1.0448          | 0.4838   | 0.4798 |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.1.1+cu121
+- Datasets 2.14.5
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "facebook/xlm-v-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",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 901629
+}

pytorch_model.bin

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training_args.bin

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