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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-300m-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-300m-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: 0.3293
- Wer: 0.2879
- Cer: 0.0927
## 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 | 3.1501 | 1.0 | 0.9865 |
| 4.3829 | 1.38 | 800 | 2.9694 | 1.0 | 0.9865 |
| 2.6389 | 2.08 | 1200 | 0.6558 | 0.5876 | 0.1878 |
| 0.9293 | 2.77 | 1600 | 0.4232 | 0.4722 | 0.1462 |
| 0.5686 | 3.46 | 2000 | 0.3513 | 0.4118 | 0.1279 |
| 0.5686 | 4.15 | 2400 | 0.3246 | 0.3994 | 0.1227 |
| 0.4388 | 4.84 | 2800 | 0.3037 | 0.3716 | 0.1158 |
| 0.3431 | 5.54 | 3200 | 0.3055 | 0.3674 | 0.1158 |
| 0.3164 | 6.23 | 3600 | 0.2973 | 0.3589 | 0.1128 |
| 0.2678 | 6.92 | 4000 | 0.3053 | 0.3421 | 0.1080 |
| 0.2678 | 7.61 | 4400 | 0.3058 | 0.3435 | 0.1083 |
| 0.2376 | 8.3 | 4800 | 0.3144 | 0.3408 | 0.1094 |
| 0.2199 | 9.0 | 5200 | 0.3177 | 0.3371 | 0.1052 |
| 0.1988 | 9.69 | 5600 | 0.3123 | 0.3299 | 0.1057 |
| 0.1816 | 10.38 | 6000 | 0.2918 | 0.3282 | 0.1049 |
| 0.1816 | 11.07 | 6400 | 0.3195 | 0.3270 | 0.1049 |
| 0.1652 | 11.76 | 6800 | 0.3080 | 0.3280 | 0.1056 |
| 0.1576 | 12.46 | 7200 | 0.2859 | 0.3218 | 0.1031 |
| 0.1558 | 13.15 | 7600 | 0.3143 | 0.3179 | 0.1018 |
| 0.1411 | 13.84 | 8000 | 0.3354 | 0.3171 | 0.1045 |
| 0.1411 | 14.53 | 8400 | 0.3285 | 0.3149 | 0.1018 |
| 0.1381 | 15.22 | 8800 | 0.3048 | 0.3138 | 0.1010 |
| 0.1178 | 15.92 | 9200 | 0.3421 | 0.3140 | 0.1012 |
| 0.1182 | 16.61 | 9600 | 0.3258 | 0.3109 | 0.1001 |
| 0.1131 | 17.3 | 10000 | 0.3220 | 0.3120 | 0.1002 |
| 0.1131 | 17.99 | 10400 | 0.3156 | 0.3098 | 0.0991 |
| 0.1031 | 18.69 | 10800 | 0.3198 | 0.3062 | 0.0980 |
| 0.1023 | 19.38 | 11200 | 0.3227 | 0.3021 | 0.0972 |
| 0.0959 | 20.07 | 11600 | 0.3187 | 0.3025 | 0.0973 |
| 0.0881 | 20.76 | 12000 | 0.3177 | 0.3004 | 0.0965 |
| 0.0881 | 21.45 | 12400 | 0.3435 | 0.2976 | 0.0960 |
| 0.0919 | 22.15 | 12800 | 0.3142 | 0.2958 | 0.0954 |
| 0.0787 | 22.84 | 13200 | 0.3010 | 0.3000 | 0.0970 |
| 0.0794 | 23.53 | 13600 | 0.3528 | 0.3008 | 0.0973 |
| 0.0751 | 24.22 | 14000 | 0.3352 | 0.2954 | 0.0961 |
| 0.0751 | 24.91 | 14400 | 0.3314 | 0.2977 | 0.0963 |
| 0.0778 | 25.61 | 14800 | 0.3214 | 0.2955 | 0.0953 |
| 0.0711 | 26.3 | 15200 | 0.3277 | 0.2936 | 0.0944 |
| 0.0681 | 26.99 | 15600 | 0.3237 | 0.2915 | 0.0940 |
| 0.0682 | 27.68 | 16000 | 0.3284 | 0.2918 | 0.0943 |
| 0.0682 | 28.37 | 16400 | 0.3304 | 0.2904 | 0.0933 |
| 0.0731 | 29.07 | 16800 | 0.3307 | 0.2881 | 0.0927 |
| 0.0619 | 29.76 | 17200 | 0.3293 | 0.2879 | 0.0927 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
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