End of training

README.md

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+---
+base_model: vinai/phobert-base-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: PhoBert_70KURL
+  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. -->
+
+# PhoBert_70KURL
+
+This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0037
+- Accuracy: 0.9983
+- F1: 0.9983
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2150
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
+| No log        | 0.4651  | 200  | 0.3962          | 0.8757   | 0.8704 |
+| No log        | 0.9302  | 400  | 0.2125          | 0.9287   | 0.9284 |
+| No log        | 1.3953  | 600  | 0.1637          | 0.9466   | 0.9466 |
+| No log        | 1.8605  | 800  | 0.1432          | 0.9526   | 0.9530 |
+| 0.321         | 2.3256  | 1000 | 0.1220          | 0.9595   | 0.9597 |
+| 0.321         | 2.7907  | 1200 | 0.1084          | 0.9638   | 0.9640 |
+| 0.321         | 3.2558  | 1400 | 0.1034          | 0.9642   | 0.9644 |
+| 0.321         | 3.7209  | 1600 | 0.0905          | 0.9693   | 0.9695 |
+| 0.129         | 4.1860  | 1800 | 0.0813          | 0.9717   | 0.9717 |
+| 0.129         | 4.6512  | 2000 | 0.0762          | 0.9745   | 0.9746 |
+| 0.129         | 5.1163  | 2200 | 0.0693          | 0.9757   | 0.9758 |
+| 0.129         | 5.5814  | 2400 | 0.0633          | 0.9782   | 0.9783 |
+| 0.0951        | 6.0465  | 2600 | 0.0657          | 0.9781   | 0.9783 |
+| 0.0951        | 6.5116  | 2800 | 0.0500          | 0.9835   | 0.9836 |
+| 0.0951        | 6.9767  | 3000 | 0.0464          | 0.9842   | 0.9843 |
+| 0.0951        | 7.4419  | 3200 | 0.0429          | 0.9857   | 0.9858 |
+| 0.0951        | 7.9070  | 3400 | 0.0417          | 0.9861   | 0.9862 |
+| 0.068         | 8.3721  | 3600 | 0.0326          | 0.9890   | 0.9890 |
+| 0.068         | 8.8372  | 3800 | 0.0296          | 0.9907   | 0.9907 |
+| 0.068         | 9.3023  | 4000 | 0.0277          | 0.9905   | 0.9905 |
+| 0.068         | 9.7674  | 4200 | 0.0237          | 0.9916   | 0.9916 |
+| 0.0484        | 10.2326 | 4400 | 0.0205          | 0.9929   | 0.9929 |
+| 0.0484        | 10.6977 | 4600 | 0.0189          | 0.9933   | 0.9933 |
+| 0.0484        | 11.1628 | 4800 | 0.0157          | 0.9944   | 0.9944 |
+| 0.0484        | 11.6279 | 5000 | 0.0145          | 0.9955   | 0.9955 |
+| 0.0356        | 12.0930 | 5200 | 0.0185          | 0.9931   | 0.9931 |
+| 0.0356        | 12.5581 | 5400 | 0.0116          | 0.9962   | 0.9962 |
+| 0.0356        | 13.0233 | 5600 | 0.0099          | 0.9964   | 0.9964 |
+| 0.0356        | 13.4884 | 5800 | 0.0103          | 0.9962   | 0.9962 |
+| 0.0356        | 13.9535 | 6000 | 0.0076          | 0.9974   | 0.9974 |
+| 0.027         | 14.4186 | 6200 | 0.0080          | 0.9971   | 0.9971 |
+| 0.027         | 14.8837 | 6400 | 0.0071          | 0.9975   | 0.9975 |
+| 0.027         | 15.3488 | 6600 | 0.0057          | 0.9980   | 0.9980 |
+| 0.027         | 15.8140 | 6800 | 0.0058          | 0.9979   | 0.9979 |
+| 0.0193        | 16.2791 | 7000 | 0.0049          | 0.9981   | 0.9981 |
+| 0.0193        | 16.7442 | 7200 | 0.0076          | 0.9973   | 0.9973 |
+| 0.0193        | 17.2093 | 7400 | 0.0051          | 0.9982   | 0.9982 |
+| 0.0193        | 17.6744 | 7600 | 0.0044          | 0.9981   | 0.9981 |
+| 0.0148        | 18.1395 | 7800 | 0.0041          | 0.9984   | 0.9984 |
+| 0.0148        | 18.6047 | 8000 | 0.0038          | 0.9984   | 0.9984 |
+| 0.0148        | 19.0698 | 8200 | 0.0039          | 0.9983   | 0.9983 |
+| 0.0148        | 19.5349 | 8400 | 0.0038          | 0.9983   | 0.9983 |
+| 0.0115        | 20.0    | 8600 | 0.0037          | 0.9983   | 0.9983 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "vinai/phobert-base-v2",
+  "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,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 258,
+  "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",
+  "tokenizer_class": "PhobertTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 64001
+}

model.safetensors

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+size 540023384

training_args.bin

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