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 +1,69 @@
+---
+license: mit
+base_model: FacebookAI/xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: reberta
+  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. -->
+
+# reberta
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3429
+- Accuracy: 0.9408
+
+## 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: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.2089        | 1.0   | 1250  | 0.1942          | 0.9408   |
+| 0.1623        | 2.0   | 2500  | 0.1801          | 0.9428   |
+| 0.1364        | 3.0   | 3750  | 0.1934          | 0.9466   |
+| 0.1051        | 4.0   | 5000  | 0.2134          | 0.9456   |
+| 0.0737        | 5.0   | 6250  | 0.2472          | 0.9446   |
+| 0.062         | 6.0   | 7500  | 0.2751          | 0.944    |
+| 0.0441        | 7.0   | 8750  | 0.2992          | 0.9422   |
+| 0.0342        | 8.0   | 10000 | 0.3116          | 0.9432   |
+| 0.026         | 9.0   | 11250 | 0.3360          | 0.943    |
+| 0.0179        | 10.0  | 12500 | 0.3429          | 0.9408   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- 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": "Finance",
+    "1": "Politics",
+    "2": "Sports",
+    "3": "Culture",
+    "4": "Medical",
+    "5": "Tech",
+    "6": "Religion"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Culture": 3,
+    "Finance": 0,
+    "Medical": 4,
+    "Politics": 1,
+    "Religion": 6,
+    "Sports": 2,
+    "Tech": 5
+  },
+  "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": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "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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+  "model_max_length": 512,
+  "pad_token": "<pad>",
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+  "tokenizer_class": "XLMRobertaTokenizer",
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+}

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