metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: w2v-bert-2.0-DF-3.0
results: []
w2v-bert-2.0-DF-3.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2216
- Accuracy: 0.9596
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: 3e-05
- train_batch_size: 42
- eval_batch_size: 42
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 168
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0314 | 1.0 | 299 | 0.2092 | 0.9542 |
| 0.0078 | 2.0 | 598 | 0.2216 | 0.9596 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.0a0+e000cf0ad9.nv24.10
- Datasets 3.1.0
- Tokenizers 0.20.3