|
--- |
|
language: |
|
- ca |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- mozilla-foundation/common_voice_8_0 |
|
- collectivat/tv3_parla |
|
- projecte-aina/parlament_parla |
|
- generated_from_trainer |
|
model-index: |
|
- name: wav2vec2-xls-r-300m-ca |
|
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-xls-r-300m-ca |
|
|
|
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_8_0 - CA dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2758 |
|
- Wer: 0.1792 |
|
|
|
## 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: 7.5e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 2000 |
|
- num_epochs: 6.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 6.2099 | 0.09 | 500 | 3.4125 | 1.0 | |
|
| 2.9961 | 0.18 | 1000 | 2.9224 | 1.0 | |
|
| 2.2147 | 0.26 | 1500 | 0.6521 | 0.5568 | |
|
| 1.3017 | 0.35 | 2000 | 0.3153 | 0.2761 | |
|
| 1.1196 | 0.44 | 2500 | 0.2444 | 0.2367 | |
|
| 1.0712 | 0.53 | 3000 | 0.2324 | 0.2132 | |
|
| 1.052 | 0.62 | 3500 | 0.2173 | 0.2032 | |
|
| 1.2813 | 2.13 | 4000 | 0.3326 | 0.2099 | |
|
| 1.2365 | 2.4 | 4500 | 0.3224 | 0.2003 | |
|
| 1.2193 | 2.66 | 5000 | 0.3198 | 0.1957 | |
|
| 1.2072 | 2.93 | 5500 | 0.3063 | 0.1933 | |
|
| 1.213 | 3.2 | 6000 | 0.3051 | 0.1980 | |
|
| 1.2074 | 3.46 | 6500 | 0.3012 | 0.1879 | |
|
| 1.1918 | 3.73 | 7000 | 0.2947 | 0.1829 | |
|
| 1.1893 | 4.0 | 7500 | 0.2895 | 0.1807 | |
|
| 1.1751 | 4.26 | 8000 | 0.2878 | 0.1776 | |
|
| 1.1628 | 4.53 | 8500 | 0.2835 | 0.1731 | |
|
| 1.1577 | 4.79 | 9000 | 0.2816 | 0.1761 | |
|
| 1.1448 | 5.06 | 9500 | 0.2757 | 0.1740 | |
|
| 1.1407 | 5.33 | 10000 | 0.2768 | 0.1798 | |
|
| 1.1401 | 5.59 | 10500 | 0.2780 | 0.1816 | |
|
| 1.1333 | 5.86 | 11000 | 0.2748 | 0.1750 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.16.0.dev0 |
|
- Pytorch 1.10.1+cu102 |
|
- Datasets 1.18.1 |
|
- Tokenizers 0.11.0 |
|
|
