metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: BERT_finetune_sentiment
results: []
BERT_finetune_sentiment
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8911
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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3369 | 1.0 | 625 | 0.2635 |
| 0.1885 | 2.0 | 1250 | 0.4271 |
| 0.1329 | 3.0 | 1875 | 0.5429 |
| 0.0545 | 4.0 | 2500 | 0.5134 |
| 0.0313 | 5.0 | 3125 | 0.6778 |
| 0.0275 | 6.0 | 3750 | 0.7123 |
| 0.0276 | 7.0 | 4375 | 0.6549 |
| 0.021 | 8.0 | 5000 | 0.6959 |
| 0.0153 | 9.0 | 5625 | 0.7736 |
| 0.0083 | 10.0 | 6250 | 0.7828 |
| 0.0111 | 11.0 | 6875 | 0.8629 |
| 0.0046 | 12.0 | 7500 | 0.8794 |
| 0.0091 | 13.0 | 8125 | 0.7696 |
| 0.0064 | 14.0 | 8750 | 0.8840 |
| 0.0035 | 15.0 | 9375 | 0.9002 |
| 0.0014 | 16.0 | 10000 | 0.9629 |
| 0.0049 | 17.0 | 10625 | 1.0240 |
| 0.0051 | 18.0 | 11250 | 0.9016 |
| 0.0021 | 19.0 | 11875 | 0.9011 |
| 0.0012 | 20.0 | 12500 | 0.8911 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1