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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-timit-xls-r-53-wandb-colab
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-timit-xls-r-53-wandb-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3325
- Wer: 0.2897
- Cer: 0.0940
## 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: 0.0001
- train_batch_size: 8
- 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: 1000
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| No log | 0.69 | 400 | 3.1507 | 1.0 | 0.9806 |
| 4.3857 | 1.38 | 800 | 3.0109 | 1.0 | 0.9806 |
| 2.6835 | 2.08 | 1200 | 0.6181 | 0.5756 | 0.1795 |
| 0.9327 | 2.77 | 1600 | 0.4239 | 0.4718 | 0.1456 |
| 0.5602 | 3.46 | 2000 | 0.3691 | 0.4141 | 0.1301 |
| 0.5602 | 4.15 | 2400 | 0.3386 | 0.3894 | 0.1231 |
| 0.4407 | 4.84 | 2800 | 0.3122 | 0.3676 | 0.1177 |
| 0.3437 | 5.54 | 3200 | 0.3149 | 0.3601 | 0.1152 |
| 0.3154 | 6.23 | 3600 | 0.3146 | 0.3495 | 0.1119 |
| 0.267 | 6.92 | 4000 | 0.3039 | 0.3427 | 0.1089 |
| 0.267 | 7.61 | 4400 | 0.3313 | 0.3409 | 0.1092 |
| 0.2354 | 8.3 | 4800 | 0.2986 | 0.3365 | 0.1064 |
| 0.2191 | 9.0 | 5200 | 0.3235 | 0.3353 | 0.1074 |
| 0.1937 | 9.69 | 5600 | 0.3117 | 0.3320 | 0.1071 |
| 0.1803 | 10.38 | 6000 | 0.3102 | 0.3233 | 0.1040 |
| 0.1803 | 11.07 | 6400 | 0.3176 | 0.3196 | 0.1030 |
| 0.1635 | 11.76 | 6800 | 0.3166 | 0.3220 | 0.1036 |
| 0.1551 | 12.46 | 7200 | 0.2836 | 0.3160 | 0.1021 |
| 0.1566 | 13.15 | 7600 | 0.3146 | 0.3186 | 0.1032 |
| 0.1424 | 13.84 | 8000 | 0.3392 | 0.3167 | 0.1036 |
| 0.1424 | 14.53 | 8400 | 0.3254 | 0.3109 | 0.1001 |
| 0.1379 | 15.22 | 8800 | 0.3249 | 0.3127 | 0.1009 |
| 0.1192 | 15.92 | 9200 | 0.3408 | 0.3119 | 0.1010 |
| 0.1178 | 16.61 | 9600 | 0.3551 | 0.3061 | 0.0997 |
| 0.1112 | 17.3 | 10000 | 0.3250 | 0.3059 | 0.0991 |
| 0.1112 | 17.99 | 10400 | 0.3127 | 0.3037 | 0.0983 |
| 0.1022 | 18.69 | 10800 | 0.3370 | 0.3067 | 0.0994 |
| 0.1031 | 19.38 | 11200 | 0.3351 | 0.3048 | 0.0991 |
| 0.0926 | 20.07 | 11600 | 0.3433 | 0.2994 | 0.0974 |
| 0.0861 | 20.76 | 12000 | 0.3145 | 0.3003 | 0.0971 |
| 0.0861 | 21.45 | 12400 | 0.3367 | 0.2980 | 0.0973 |
| 0.0935 | 22.15 | 12800 | 0.3139 | 0.3016 | 0.0986 |
| 0.0784 | 22.84 | 13200 | 0.3181 | 0.2990 | 0.0972 |
| 0.078 | 23.53 | 13600 | 0.3347 | 0.2938 | 0.0961 |
| 0.0761 | 24.22 | 14000 | 0.3371 | 0.2921 | 0.0949 |
| 0.0761 | 24.91 | 14400 | 0.3274 | 0.2916 | 0.0952 |
| 0.0784 | 25.61 | 14800 | 0.3152 | 0.2927 | 0.0942 |
| 0.0714 | 26.3 | 15200 | 0.3237 | 0.2924 | 0.0943 |
| 0.0671 | 26.99 | 15600 | 0.3183 | 0.2914 | 0.0945 |
| 0.0684 | 27.68 | 16000 | 0.3307 | 0.2931 | 0.0950 |
| 0.0684 | 28.37 | 16400 | 0.3383 | 0.2913 | 0.0940 |
| 0.07 | 29.07 | 16800 | 0.3318 | 0.2901 | 0.0940 |
| 0.0624 | 29.76 | 17200 | 0.3325 | 0.2897 | 0.0940 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
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