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ModeloFT1-v1

Text Classification
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roberta
Generated from Trainer
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End of training

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  1. README.md +85 -0
  2. config.json +40 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: projecte-aina/roberta-base-ca-v2-cawikitc
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: stocks
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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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+ # stocks
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+
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+ This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cawikitc](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cawikitc) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6639
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+ - Accuracy: 0.7637
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+ - Precision: 0.5304
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+ - Recall: 0.4710
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+ - F1: 0.4778
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+ - Ratio: 0.7903
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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: 2e-05
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+ - train_batch_size: 10
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 20
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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_ratio: 0.06
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+ - lr_scheduler_warmup_steps: 4
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+ - num_epochs: 1
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+ - label_smoothing_factor: 0.1
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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 | Precision | Recall | F1 | Ratio |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | 0.8468 | 0.07 | 10 | 0.8350 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
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+ | 0.7922 | 0.14 | 20 | 0.8314 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
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+ | 0.8005 | 0.21 | 30 | 0.8059 | 0.6169 | 0.2060 | 0.3325 | 0.2544 | 0.9984 |
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+ | 0.8038 | 0.28 | 40 | 0.7907 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
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+ | 0.7846 | 0.34 | 50 | 0.8060 | 0.6185 | 0.3093 | 0.5 | 0.3822 | 1.0 |
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+ | 0.7539 | 0.41 | 60 | 0.7573 | 0.6274 | 0.5024 | 0.3422 | 0.2763 | 0.9847 |
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+ | 0.725 | 0.48 | 70 | 0.8018 | 0.7435 | 0.4978 | 0.4906 | 0.4940 | 0.5847 |
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+ | 0.6842 | 0.55 | 80 | 0.8437 | 0.7419 | 0.5035 | 0.4795 | 0.4901 | 0.6444 |
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+ | 0.7415 | 0.62 | 90 | 0.7783 | 0.7468 | 0.5006 | 0.4832 | 0.4909 | 0.6444 |
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+ | 0.6303 | 0.69 | 100 | 0.7194 | 0.7452 | 0.5009 | 0.4723 | 0.4808 | 0.7040 |
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+ | 0.6844 | 0.76 | 110 | 0.7137 | 0.7702 | 0.5106 | 0.4996 | 0.5044 | 0.6468 |
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+ | 0.699 | 0.83 | 120 | 0.6666 | 0.7806 | 0.5159 | 0.5039 | 0.5084 | 0.6653 |
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+ | 0.7229 | 0.9 | 130 | 0.6636 | 0.7629 | 0.5233 | 0.4730 | 0.4799 | 0.775 |
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+ | 0.6555 | 0.97 | 140 | 0.6646 | 0.7637 | 0.5312 | 0.4707 | 0.4775 | 0.7919 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.15.2
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+ "gradient_checkpointing": false,
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+ "id2label": {
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+ "0": "entailment",
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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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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+ "type_vocab_size": 1,
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+ "vocab_size": 52253
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+ }
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