---
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: 1.5563
- Wer: 0.8702

## 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: 128
- 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.3096 | 100  | 3.5623          | 1.0    |
| No log        | 0.6192 | 200  | 3.1175          | 1.0    |
| No log        | 0.9288 | 300  | 3.2933          | 1.0    |
| No log        | 1.2384 | 400  | 0.9765          | 0.6866 |
| 3.7398        | 1.5480 | 500  | 0.6787          | 0.4922 |
| 3.7398        | 1.8576 | 600  | 0.6015          | 0.4347 |
| 3.7398        | 2.1672 | 700  | 0.5699          | 0.4273 |
| 3.7398        | 2.4768 | 800  | 0.5419          | 0.3958 |
| 3.7398        | 2.7864 | 900  | 0.4971          | 0.3730 |
| 0.5228        | 3.0960 | 1000 | 0.4960          | 0.3543 |
| 0.5228        | 3.4056 | 1100 | 0.6977          | 0.4655 |
| 0.5228        | 3.7152 | 1200 | 0.7999          | 0.5316 |
| 0.5228        | 4.0248 | 1300 | 1.0526          | 0.6215 |
| 0.5228        | 4.3344 | 1400 | 1.1285          | 0.7572 |
| 0.9047        | 4.6440 | 1500 | 1.1593          | 0.7047 |
| 0.9047        | 4.9536 | 1600 | 2.0401          | 0.9667 |
| 0.9047        | 5.2632 | 1700 | 1.6264          | 0.8680 |
| 0.9047        | 5.5728 | 1800 | 1.5916          | 0.8627 |
| 0.9047        | 5.8824 | 1900 | 1.5764          | 0.8720 |
| 1.6715        | 6.1920 | 2000 | 1.5563          | 0.8702 |


### Framework versions

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