---
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: 0.5324
- Wer: 0.4014

## 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: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 4.7051        | 0.0321 | 500   | 1.7504          | 0.9570 |
| 1.0409        | 0.0641 | 1000  | 1.1511          | 0.7761 |
| 0.8183        | 0.0962 | 1500  | 1.0506          | 0.7097 |
| 0.7091        | 0.1283 | 2000  | 0.9421          | 0.6610 |
| 0.6547        | 0.1603 | 2500  | 0.8726          | 0.6128 |
| 0.6088        | 0.1924 | 3000  | 0.8246          | 0.5990 |
| 0.5781        | 0.2244 | 3500  | 0.8025          | 0.5747 |
| 0.5429        | 0.2565 | 4000  | 0.7360          | 0.5305 |
| 0.5104        | 0.2886 | 4500  | 0.7335          | 0.5394 |
| 0.501         | 0.3206 | 5000  | 0.6933          | 0.5088 |
| 0.4708        | 0.3527 | 5500  | 0.6770          | 0.5113 |
| 0.4526        | 0.3848 | 6000  | 0.6609          | 0.4806 |
| 0.4235        | 0.4168 | 6500  | 0.6373          | 0.4858 |
| 0.4032        | 0.4489 | 7000  | 0.6048          | 0.4466 |
| 0.3863        | 0.4810 | 7500  | 0.5946          | 0.4432 |
| 0.3766        | 0.5130 | 8000  | 0.5737          | 0.4298 |
| 0.3746        | 0.5451 | 8500  | 0.5668          | 0.4248 |
| 0.3586        | 0.5771 | 9000  | 0.5485          | 0.4101 |
| 0.3552        | 0.6092 | 9500  | 0.5378          | 0.4032 |
| 0.3326        | 0.6413 | 10000 | 0.5324          | 0.4014 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1