pytorch tensorboard wav2vec2 automatic-speech-recognition transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-robust-ft-timit
  results: []
---

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# wav2vec2-large-robust-ft-timit

This model is a fine-tuned version of [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2768
- Wer: 0.2321

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.6175        | 1.0   | 500   | 3.3025          | 1.0    |
| 3.0746        | 2.01  | 1000  | 2.9598          | 1.0    |
| 1.967         | 3.01  | 1500  | 0.6760          | 0.5607 |
| 0.7545        | 4.02  | 2000  | 0.4500          | 0.4567 |
| 0.5415        | 5.02  | 2500  | 0.3702          | 0.3882 |
| 0.4445        | 6.02  | 3000  | 0.3421          | 0.3584 |
| 0.3601        | 7.03  | 3500  | 0.2947          | 0.3096 |
| 0.3098        | 8.03  | 4000  | 0.2740          | 0.2894 |
| 0.2606        | 9.04  | 4500  | 0.2725          | 0.2787 |
| 0.238         | 10.04 | 5000  | 0.2549          | 0.2617 |
| 0.2142        | 11.04 | 5500  | 0.2485          | 0.2530 |
| 0.1787        | 12.05 | 6000  | 0.2683          | 0.2514 |
| 0.1652        | 13.05 | 6500  | 0.2559          | 0.2476 |
| 0.1569        | 14.06 | 7000  | 0.2777          | 0.2470 |
| 0.1443        | 15.06 | 7500  | 0.2661          | 0.2431 |
| 0.1335        | 16.06 | 8000  | 0.2717          | 0.2422 |
| 0.1291        | 17.07 | 8500  | 0.2672          | 0.2428 |
| 0.1192        | 18.07 | 9000  | 0.2684          | 0.2395 |
| 0.1144        | 19.08 | 9500  | 0.2770          | 0.2411 |
| 0.1052        | 20.08 | 10000 | 0.2831          | 0.2379 |
| 0.1004        | 21.08 | 10500 | 0.2847          | 0.2375 |
| 0.1053        | 22.09 | 11000 | 0.2851          | 0.2360 |
| 0.1005        | 23.09 | 11500 | 0.2807          | 0.2361 |
| 0.0904        | 24.1  | 12000 | 0.2764          | 0.2346 |
| 0.0876        | 25.1  | 12500 | 0.2774          | 0.2325 |
| 0.0883        | 26.1  | 13000 | 0.2768          | 0.2313 |
| 0.0848        | 27.11 | 13500 | 0.2840          | 0.2307 |
| 0.0822        | 28.11 | 14000 | 0.2812          | 0.2316 |
| 0.09          | 29.12 | 14500 | 0.2768          | 0.2321 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.8.2+cu111
- Datasets 1.17.0
- Tokenizers 0.11.6
