metadata

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: []

wav2vec2-xls-r-300m-ca

This model is a fine-tuned version of 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