End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- ag_news
+metrics:
+- accuracy
+model-index:
+- name: roberta-base_ag_news
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: ag_news
+      type: ag_news
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8957894736842106
+---
+
+<!-- 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. -->
+
+# roberta-base_ag_news
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the ag_news dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4418
+- Accuracy: 0.8958
+- F1-score: 0.8952
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 0.4326        | 1.0   | 500  | 0.5287          | 0.8921   | 0.8914   |
+| 0.2381        | 2.0   | 1000 | 0.4418          | 0.8958   | 0.8952   |
+| 0.095         | 3.0   | 1500 | 0.5376          | 0.8937   | 0.8932   |
+| 0.1567        | 4.0   | 2000 | 0.4580          | 0.9084   | 0.9082   |
+| 0.1069        | 5.0   | 2500 | 0.4800          | 0.9132   | 0.9129   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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special_tokens_map.json

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+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+      "lstrip": false,
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+      "single_word": false,
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+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}