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Acc0.8607990012484394, F10.8614809399603419 , Augmented with bert-base-uncased.csv, finetuned on ProsusAI/finbert

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  1. README.md +87 -0
  2. config.json +37 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ base_model: ProsusAI/finbert
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: finbert_bert-base-uncased
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+ results: []
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+ ---
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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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+
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+ # finbert_bert-base-uncased
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+
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+ This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8116
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+ - Accuracy: 0.8752
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+ - F1: 0.8758
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+ - Precision: 0.8778
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+ - Recall: 0.8752
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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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+ - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.8465 | 1.0 | 91 | 0.7610 | 0.6817 | 0.6643 | 0.6806 | 0.6817 |
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+ | 0.5154 | 2.0 | 182 | 0.4672 | 0.8066 | 0.8082 | 0.8203 | 0.8066 |
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+ | 0.331 | 3.0 | 273 | 0.4259 | 0.8393 | 0.8396 | 0.8407 | 0.8393 |
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+ | 0.2461 | 4.0 | 364 | 0.5386 | 0.8315 | 0.8311 | 0.8405 | 0.8315 |
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+ | 0.163 | 5.0 | 455 | 0.5392 | 0.8518 | 0.8496 | 0.8554 | 0.8518 |
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+ | 0.1193 | 6.0 | 546 | 0.5441 | 0.8565 | 0.8559 | 0.8590 | 0.8565 |
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+ | 0.0935 | 7.0 | 637 | 0.6496 | 0.8253 | 0.8218 | 0.8306 | 0.8253 |
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+ | 0.0536 | 8.0 | 728 | 0.5461 | 0.8612 | 0.8609 | 0.8609 | 0.8612 |
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+ | 0.0809 | 9.0 | 819 | 0.6680 | 0.8362 | 0.8350 | 0.8394 | 0.8362 |
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+ | 0.0986 | 10.0 | 910 | 0.6303 | 0.8596 | 0.8597 | 0.8645 | 0.8596 |
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+ | 0.0765 | 11.0 | 1001 | 0.7653 | 0.8300 | 0.8310 | 0.8511 | 0.8300 |
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+ | 0.0507 | 12.0 | 1092 | 0.5176 | 0.8690 | 0.8691 | 0.8701 | 0.8690 |
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+ | 0.0633 | 13.0 | 1183 | 0.9141 | 0.8268 | 0.8261 | 0.8370 | 0.8268 |
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+ | 0.0529 | 14.0 | 1274 | 0.7537 | 0.8549 | 0.8552 | 0.8621 | 0.8549 |
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+ | 0.0418 | 15.0 | 1365 | 0.9200 | 0.8346 | 0.8342 | 0.8441 | 0.8346 |
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+ | 0.0151 | 16.0 | 1456 | 0.8578 | 0.8565 | 0.8549 | 0.8622 | 0.8565 |
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+ | 0.0154 | 17.0 | 1547 | 0.8116 | 0.8752 | 0.8758 | 0.8778 | 0.8752 |
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+ | 0.0054 | 18.0 | 1638 | 0.8926 | 0.8736 | 0.8733 | 0.8751 | 0.8736 |
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+ | 0.0259 | 19.0 | 1729 | 0.9026 | 0.8705 | 0.8705 | 0.8709 | 0.8705 |
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+ | 0.0036 | 20.0 | 1820 | 0.9616 | 0.8721 | 0.8713 | 0.8716 | 0.8721 |
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+ | 0.0012 | 21.0 | 1911 | 0.9985 | 0.8658 | 0.8656 | 0.8655 | 0.8658 |
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+ | 0.002 | 22.0 | 2002 | 0.9833 | 0.8690 | 0.8689 | 0.8688 | 0.8690 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.0
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+ - Pytorch 2.1.2
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+ - Datasets 2.1.0
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+ - Tokenizers 0.15.1
config.json ADDED
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+ {
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+ "_name_or_path": "ProsusAI/finbert",
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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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+ "gradient_checkpointing": false,
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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": "positive",
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+ "1": "negative",
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+ "2": "neutral"
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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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+ "neutral": 2,
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+ "positive": 0
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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": "4.37.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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