End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: RoBERTa_EmpAI_Definitivo
+  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. -->
+
+# RoBERTa_EmpAI_Definitivo
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 13
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 1.0   | 483  | 1.0998          |
+| 1.286         | 2.0   | 967  | 1.0487          |
+| 1.1701        | 3.0   | 1450 | 1.0243          |
+| 1.1044        | 4.0   | 1934 | 1.0189          |
+| 1.0555        | 5.0   | 2417 | 1.0084          |
+| 1.0418        | 6.0   | 2901 | 1.0030          |
+| 1.0181        | 7.0   | 3384 | 1.0207          |
+| 1.023         | 7.99  | 3864 | 0.9954          |
+| 1.018         | 9.0   | 4347 | 0.9925          |
+| 1.0144        | 10.0  | 4831 | 0.9842          |
+| 1.0024        | 11.0  | 5314 | 0.9665          |
+| 1.0003        | 12.0  | 5798 | 0.9864          |
+| 0.9924        | 12.99 | 6279 | 0.9767          |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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