---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-normalized
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-bert-ft-btb-cy
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# w2v2-bert-ft-btb-cy

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-NORMALIZED - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9375
- Wer: 1.0

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---:|
| No log        | 0.1414 | 100  | 6.9702          | 1.0 |
| No log        | 0.2829 | 200  | 3.3676          | 1.0 |
| No log        | 0.4243 | 300  | 3.0393          | 1.0 |
| No log        | 0.5658 | 400  | 2.9887          | 1.0 |
| 4.717         | 0.7072 | 500  | 3.0227          | 1.0 |
| 4.717         | 0.8487 | 600  | 3.0406          | 1.0 |
| 4.717         | 0.9901 | 700  | 3.0029          | 1.0 |
| 4.717         | 1.1315 | 800  | 2.9483          | 1.0 |
| 4.717         | 1.2730 | 900  | 2.9511          | 1.0 |
| 3.0065        | 1.4144 | 1000 | 2.9473          | 1.0 |
| 3.0065        | 1.5559 | 1100 | 2.9448          | 1.0 |
| 3.0065        | 1.6973 | 1200 | 2.9470          | 1.0 |
| 3.0065        | 1.8388 | 1300 | 2.9446          | 1.0 |
| 3.0065        | 1.9802 | 1400 | 2.9432          | 1.0 |
| 2.9634        | 2.1216 | 1500 | 2.9476          | 1.0 |
| 2.9634        | 2.2631 | 1600 | 2.9624          | 1.0 |
| 2.9634        | 2.4045 | 1700 | 2.9581          | 1.0 |
| 2.9634        | 2.5460 | 1800 | 2.9553          | 1.0 |
| 2.9634        | 2.6874 | 1900 | 2.9515          | 1.0 |
| 2.9677        | 2.8289 | 2000 | 2.9481          | 1.0 |
| 2.9677        | 2.9703 | 2100 | 2.9509          | 1.0 |
| 2.9677        | 3.1117 | 2200 | 2.9408          | 1.0 |
| 2.9677        | 3.2532 | 2300 | 2.9393          | 1.0 |
| 2.9677        | 3.3946 | 2400 | 2.9381          | 1.0 |
| 2.9612        | 3.5361 | 2500 | 2.9375          | 1.0 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1