clasificador-tweets
This model is a fine-tuned version of mrm8488/electricidad-base-discriminator on the somosnlp-hackathon-2022/es_tweets_laboral dataset. It achieves the following results on the evaluation set:
- Loss: 1.4954
- Accuracy: 0.7021
Intended uses & limitations
This model is intended for the task Text Classification.
Training and evaluation data
We used the somosnlp-hackathon-2022/es_tweets_laboral dataset.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 23 | 1.2185 | 0.6383 |
No log | 2.0 | 46 | 1.2849 | 0.6596 |
No log | 3.0 | 69 | 1.4492 | 0.5957 |
No log | 4.0 | 92 | 1.1863 | 0.7234 |
No log | 5.0 | 115 | 1.5050 | 0.6383 |
No log | 6.0 | 138 | 1.4848 | 0.6383 |
No log | 7.0 | 161 | 1.5045 | 0.7021 |
No log | 8.0 | 184 | 1.5510 | 0.6809 |
No log | 9.0 | 207 | 1.4867 | 0.7021 |
No log | 10.0 | 230 | 1.4954 | 0.7021 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
mrm8488/electricidad-base-discriminator