---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-ccv-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. -->

# wav2vec2-xlsr-53-ft-btb-ccv-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4971
- Wer: 0.3381

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.1548 | 100  | 3.5561          | 1.0    |
| No log        | 0.3096 | 200  | 3.3712          | 1.0    |
| No log        | 0.4644 | 300  | 3.1736          | 1.0    |
| No log        | 0.6192 | 400  | 1.1719          | 0.7910 |
| 3.7217        | 0.7740 | 500  | 0.9169          | 0.6776 |
| 3.7217        | 0.9288 | 600  | 0.8097          | 0.6191 |
| 3.7217        | 1.0836 | 700  | 0.6986          | 0.5080 |
| 3.7217        | 1.2384 | 800  | 0.6123          | 0.4629 |
| 3.7217        | 1.3932 | 900  | 0.5815          | 0.4499 |
| 0.6148        | 1.5480 | 1000 | 0.5666          | 0.4218 |
| 0.6148        | 1.7028 | 1100 | 0.5285          | 0.4049 |
| 0.6148        | 1.8576 | 1200 | 0.5309          | 0.3972 |
| 0.6148        | 2.0124 | 1300 | 0.4993          | 0.3818 |
| 0.6148        | 2.1672 | 1400 | 0.4779          | 0.3722 |
| 0.4634        | 2.3220 | 1500 | 0.4679          | 0.3659 |
| 0.4634        | 2.4768 | 1600 | 0.4679          | 0.3621 |
| 0.4634        | 2.6316 | 1700 | 0.4525          | 0.3504 |
| 0.4634        | 2.7864 | 1800 | 0.4353          | 0.3357 |
| 0.4634        | 2.9412 | 1900 | 0.4358          | 0.3423 |
| 0.3708        | 3.0960 | 2000 | 0.4391          | 0.3355 |
| 0.3708        | 3.2508 | 2100 | 0.4307          | 0.3282 |
| 0.3708        | 3.4056 | 2200 | 0.4274          | 0.3275 |
| 0.3708        | 3.5604 | 2300 | 0.4388          | 0.3246 |
| 0.3708        | 3.7152 | 2400 | 0.4521          | 0.3277 |
| 0.3391        | 3.8700 | 2500 | 0.4861          | 0.3390 |
| 0.3391        | 4.0248 | 2600 | 0.4971          | 0.3381 |


### Framework versions

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