metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-timit-demo-google-colab
results: []
wav2vec2-base-timit-demo-google-colab
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5328
- Wer: 0.2175
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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
3.4608 | 1.0 | 500 | 1.4610 | 0.9290 |
0.796 | 2.01 | 1000 | 0.5283 | 0.4217 |
0.4219 | 3.01 | 1500 | 0.4277 | 0.3353 |
0.2919 | 4.02 | 2000 | 0.4154 | 0.3102 |
0.2263 | 5.02 | 2500 | 0.4096 | 0.2954 |
0.1885 | 6.02 | 3000 | 0.4274 | 0.2944 |
0.1595 | 7.03 | 3500 | 0.4529 | 0.2681 |
0.1371 | 8.03 | 4000 | 0.4309 | 0.2721 |
0.1218 | 9.04 | 4500 | 0.4574 | 0.2629 |
0.1118 | 10.04 | 5000 | 0.5396 | 0.2605 |
0.0988 | 11.04 | 5500 | 0.5031 | 0.2683 |
0.0944 | 12.05 | 6000 | 0.5040 | 0.2595 |
0.0781 | 13.05 | 6500 | 0.4909 | 0.2611 |
0.0714 | 14.06 | 7000 | 0.4740 | 0.2635 |
0.0648 | 15.06 | 7500 | 0.4613 | 0.2509 |
0.0628 | 16.06 | 8000 | 0.4731 | 0.2508 |
0.0539 | 17.07 | 8500 | 0.5100 | 0.2448 |
0.0542 | 18.07 | 9000 | 0.5048 | 0.2507 |
0.0453 | 19.08 | 9500 | 0.5290 | 0.2466 |
0.0446 | 20.08 | 10000 | 0.5482 | 0.2398 |
0.0405 | 21.08 | 10500 | 0.5768 | 0.2422 |
0.0368 | 22.09 | 11000 | 0.5848 | 0.2403 |
0.0349 | 23.09 | 11500 | 0.5469 | 0.2321 |
0.0326 | 24.1 | 12000 | 0.5618 | 0.2294 |
0.028 | 25.1 | 12500 | 0.5590 | 0.2297 |
0.0254 | 26.1 | 13000 | 0.5531 | 0.2291 |
0.0258 | 27.11 | 13500 | 0.5302 | 0.2215 |
0.0244 | 28.11 | 14000 | 0.5388 | 0.2188 |
0.0195 | 29.12 | 14500 | 0.5328 | 0.2175 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 1.18.3
- Tokenizers 0.15.0