ChunLok/Cam_Bert_model
Browse files- README.md +63 -0
- config.json +42 -0
- model.safetensors +3 -0
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README.md
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---
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base_model: yiyanghkust/finbert-pretrain
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: temp
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# temp
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This model is a fine-tuned version of [yiyanghkust/finbert-pretrain](https://huggingface.co/yiyanghkust/finbert-pretrain) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8959
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- Accuracy: 0.7025
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.1172 | 1.0 | 753 | 1.0053 | 0.5396 |
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| 0.8259 | 2.0 | 1506 | 0.8250 | 0.6472 |
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| 0.6817 | 3.0 | 2259 | 0.8871 | 0.6487 |
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| 0.5578 | 4.0 | 3012 | 0.8300 | 0.6891 |
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| 0.4379 | 5.0 | 3765 | 0.8959 | 0.7025 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "yiyanghkust/finbert-pretrain",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "VERY NEGATIVE",
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"1": "NEGATIVE",
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"2": "SLIGHTLY NEGATIVE",
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"3": "SLIGHTLY POSITIVE",
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"4": "POSITIVE",
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"5": "VERY POSITIVE"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"NEGATIVE": 1,
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"POSITIVE": 4,
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"SLIGHTLY NEGATIVE": 2,
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"SLIGHTLY POSITIVE": 3,
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"VERY NEGATIVE": 0,
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"VERY POSITIVE": 5
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.36.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30873
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}
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model.safetensors
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