metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: nlptown/bert-base-multilingual-uncased-sentiment
model-index:
- name: model_IMDB_bert_base_peft
results: []
model_IMDB_bert_base_peft
This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2116
- Accuracy: 0.9224
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2559 | 1.0 | 1563 | 0.2355 | 0.9088 |
| 0.2406 | 2.0 | 3126 | 0.2285 | 0.9134 |
| 0.2322 | 3.0 | 4689 | 0.2185 | 0.9173 |
| 0.2291 | 4.0 | 6252 | 0.2174 | 0.9193 |
| 0.2177 | 5.0 | 7815 | 0.2171 | 0.9186 |
| 0.2218 | 6.0 | 9378 | 0.2154 | 0.9202 |
| 0.2116 | 7.0 | 10941 | 0.2127 | 0.9221 |
| 0.2133 | 8.0 | 12504 | 0.2101 | 0.9225 |
| 0.2076 | 9.0 | 14067 | 0.2125 | 0.9221 |
| 0.2029 | 10.0 | 15630 | 0.2116 | 0.9224 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2