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---
language:
- cy
license: apache-2.0
tags:
- automatic-speech-recognition
- cy
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Welsh
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: cy
metrics:
- name: Test WER
type: wer
value: 31.003
- name: Test CER
type: cer
value: 7.775
---
<!-- 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-large-xls-r-300m-welsh
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - CY dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2650
- Wer: 0.2702
## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.3454 | 8.2 | 3000 | 0.4926 | 0.5703 |
| 1.1202 | 16.39 | 6000 | 0.3529 | 0.3944 |
| 1.0058 | 24.59 | 9000 | 0.3143 | 0.3341 |
| 0.9287 | 32.79 | 12000 | 0.2896 | 0.2980 |
| 0.8849 | 40.98 | 15000 | 0.2727 | 0.2798 |
| 0.8665 | 49.18 | 18000 | 0.2662 | 0.2696 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0