Joi123/Vietnamese-social-media-visobert

README.md

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+---
+base_model: 5CD-AI/Vietnamese-Sentiment-visobert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: Vietnamese-social-media-visobert
+  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. -->
+
+# Vietnamese-social-media-visobert
+
+This model is a fine-tuned version of [5CD-AI/Vietnamese-Sentiment-visobert](https://huggingface.co/5CD-AI/Vietnamese-Sentiment-visobert) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8985
+- Accuracy: 0.8744
+- F1: 0.8264
+- Precision: 0.8363
+- Recall: 0.8175
+
+## 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: 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: 260
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 0.3817 | 50   | 0.6882          | 0.8117   | 0.7660 | 0.7615    | 0.7709 |
+| No log        | 0.7634 | 100  | 0.5681          | 0.8386   | 0.7849 | 0.8154    | 0.7628 |
+| 0.9396        | 1.1450 | 150  | 0.5227          | 0.8520   | 0.8116 | 0.8157    | 0.8083 |
+| 0.9396        | 1.5267 | 200  | 0.5717          | 0.8475   | 0.8039 | 0.8007    | 0.8135 |
+| 0.9396        | 1.9084 | 250  | 0.5705          | 0.8251   | 0.7842 | 0.7896    | 0.7825 |
+| 0.4081        | 2.2901 | 300  | 0.6703          | 0.8565   | 0.8217 | 0.8251    | 0.8208 |
+| 0.4081        | 2.6718 | 350  | 0.7260          | 0.8610   | 0.8162 | 0.8351    | 0.8016 |
+| 0.2027        | 3.0534 | 400  | 0.6946          | 0.8610   | 0.8148 | 0.8152    | 0.8155 |
+| 0.2027        | 3.4351 | 450  | 0.8426          | 0.8520   | 0.7935 | 0.8183    | 0.7747 |
+| 0.2027        | 3.8168 | 500  | 0.8195          | 0.8520   | 0.7828 | 0.8255    | 0.7610 |
+| 0.1098        | 4.1985 | 550  | 0.8272          | 0.8520   | 0.8072 | 0.8171    | 0.7984 |
+| 0.1098        | 4.5802 | 600  | 0.9978          | 0.8520   | 0.7925 | 0.8361    | 0.7648 |
+| 0.0277        | 4.9618 | 650  | 0.8102          | 0.8430   | 0.7882 | 0.8029    | 0.7796 |
+| 0.0277        | 5.3435 | 700  | 0.8563          | 0.8520   | 0.7926 | 0.8107    | 0.7787 |
+| 0.0277        | 5.7252 | 750  | 0.9299          | 0.8565   | 0.8052 | 0.8291    | 0.7871 |
+| 0.0089        | 6.1069 | 800  | 0.8562          | 0.8520   | 0.8002 | 0.8141    | 0.7886 |
+| 0.0089        | 6.4885 | 850  | 0.8737          | 0.8610   | 0.8074 | 0.8213    | 0.7958 |
+| 0.0089        | 6.8702 | 900  | 0.9388          | 0.8610   | 0.8079 | 0.8431    | 0.7839 |
+| 0.0094        | 7.2519 | 950  | 0.9036          | 0.8744   | 0.8280 | 0.8540    | 0.8097 |
+| 0.0094        | 7.6336 | 1000 | 0.9003          | 0.8744   | 0.8264 | 0.8363    | 0.8175 |
+| 0.0052        | 8.0153 | 1050 | 0.8814          | 0.8744   | 0.8264 | 0.8363    | 0.8175 |
+| 0.0052        | 8.3969 | 1100 | 0.8918          | 0.8744   | 0.8264 | 0.8363    | 0.8175 |
+| 0.0052        | 8.7786 | 1150 | 0.8964          | 0.8744   | 0.8264 | 0.8363    | 0.8175 |
+| 0.0055        | 9.1603 | 1200 | 0.8936          | 0.8744   | 0.8264 | 0.8363    | 0.8175 |
+| 0.0055        | 9.5420 | 1250 | 0.8959          | 0.8744   | 0.8264 | 0.8363    | 0.8175 |
+| 0.0079        | 9.9237 | 1300 | 0.8985          | 0.8744   | 0.8264 | 0.8363    | 0.8175 |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.4.0+cu121
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "5CD-AI/Vietnamese-Sentiment-visobert",
+  "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": "NEG",
+    "1": "POS",
+    "2": "NEU"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "NEG": 0,
+    "NEU": 2,
+    "POS": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 256,
+  "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": "4.43.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 15004
+}

model.safetensors

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+oid sha256:184ad57754cfd7068f16909aefb9008e3c85e95fed71719eee0a78c4f6a775a2
+size 390297116

training_args.bin

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