hc3-wiki-domain-classification-roberta-1-epoch

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: hc3-wiki-domain-classification-roberta
+  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. -->
+
+# hc3-wiki-domain-classification-roberta
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1821
+- Accuracy: 0.9810
+- F1 Score: 0.9810
+
+## 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: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Score |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
+| 0.5388        | 0.04  | 400   | 0.3470          | 0.9626   | 0.9626   |
+| 0.4795        | 0.08  | 800   | 0.4603          | 0.9659   | 0.9659   |
+| 0.4419        | 0.12  | 1200  | 0.3184          | 0.9622   | 0.9622   |
+| 0.3985        | 0.15  | 1600  | 0.3919          | 0.9697   | 0.9697   |
+| 0.3954        | 0.19  | 2000  | 0.3571          | 0.9718   | 0.9718   |
+| 0.4891        | 0.23  | 2400  | 0.4775          | 0.9668   | 0.9668   |
+| 0.4283        | 0.27  | 2800  | 0.3616          | 0.9677   | 0.9677   |
+| 0.4157        | 0.31  | 3200  | 0.4152          | 0.9519   | 0.9519   |
+| 0.4477        | 0.35  | 3600  | 0.3460          | 0.9673   | 0.9673   |
+| 0.426         | 0.39  | 4000  | 0.4334          | 0.9669   | 0.9669   |
+| 0.3704        | 0.43  | 4400  | 0.3405          | 0.9634   | 0.9634   |
+| 0.4027        | 0.46  | 4800  | 0.3232          | 0.9738   | 0.9738   |
+| 0.3704        | 0.5   | 5200  | 0.3475          | 0.9672   | 0.9672   |
+| 0.3459        | 0.54  | 5600  | 0.4094          | 0.9738   | 0.9738   |
+| 0.3707        | 0.58  | 6000  | 0.3176          | 0.9703   | 0.9703   |
+| 0.3145        | 0.62  | 6400  | 0.3329          | 0.9760   | 0.9760   |
+| 0.3153        | 0.66  | 6800  | 0.3762          | 0.9733   | 0.9733   |
+| 0.293         | 0.7   | 7200  | 0.2815          | 0.9761   | 0.9761   |
+| 0.2981        | 0.74  | 7600  | 0.2577          | 0.9771   | 0.9771   |
+| 0.2481        | 0.77  | 8000  | 0.2134          | 0.9780   | 0.9780   |
+| 0.2418        | 0.81  | 8400  | 0.1978          | 0.9779   | 0.9779   |
+| 0.2235        | 0.85  | 8800  | 0.1896          | 0.9794   | 0.9794   |
+| 0.1934        | 0.89  | 9200  | 0.1895          | 0.9796   | 0.9796   |
+| 0.2167        | 0.93  | 9600  | 0.1804          | 0.9792   | 0.9792   |
+| 0.1992        | 0.97  | 10000 | 0.1821          | 0.9810   | 0.9810   |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.0.0
+- Datasets 2.13.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "roberta-base",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "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": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

pytorch_model.bin

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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,
+  "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>"
+}

training_args.bin

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