---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v-bert-2.0-DF-3.0

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/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