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beto-sentiment-analysis-finetuned-onpremise
This model is a fine-tuned version of finiteautomata/beto-sentiment-analysis on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7939
- Accuracy: 0.8301
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4573 | 1.0 | 1250 | 0.4375 | 0.8191 |
| 0.2191 | 2.0 | 2500 | 0.5367 | 0.8288 |
| 0.1164 | 3.0 | 3750 | 0.7939 | 0.8301 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 1.18.4
- Tokenizers 0.12.1
