File size: 2,717 Bytes
cfba09e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- vivos_dataset
model-index:
- name: wav2vec2-base-vios-v4
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-base-vios-v4
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the vivos_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3198
- Wer: 0.2169
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 7.8138 | 0.69 | 500 | 3.5011 | 1.0 |
| 3.4372 | 1.37 | 1000 | 3.3447 | 1.0 |
| 1.9519 | 2.06 | 1500 | 0.8356 | 0.5944 |
| 0.8581 | 2.74 | 2000 | 0.5280 | 0.4038 |
| 0.6405 | 3.43 | 2500 | 0.4410 | 0.3410 |
| 0.5417 | 4.12 | 3000 | 0.3990 | 0.3140 |
| 0.4804 | 4.8 | 3500 | 0.3804 | 0.2973 |
| 0.4384 | 5.49 | 4000 | 0.3644 | 0.2808 |
| 0.4162 | 6.17 | 4500 | 0.3542 | 0.2648 |
| 0.3941 | 6.86 | 5000 | 0.3436 | 0.2529 |
| 0.3733 | 7.54 | 5500 | 0.3355 | 0.2520 |
| 0.3564 | 8.23 | 6000 | 0.3294 | 0.2415 |
| 0.3412 | 8.92 | 6500 | 0.3311 | 0.2332 |
| 0.3266 | 9.6 | 7000 | 0.3217 | 0.2325 |
| 0.3226 | 10.29 | 7500 | 0.3317 | 0.2303 |
| 0.3115 | 10.97 | 8000 | 0.3226 | 0.2279 |
| 0.3094 | 11.66 | 8500 | 0.3157 | 0.2236 |
| 0.2967 | 12.35 | 9000 | 0.3109 | 0.2202 |
| 0.2995 | 13.03 | 9500 | 0.3129 | 0.2156 |
| 0.2895 | 13.72 | 10000 | 0.3195 | 0.2146 |
| 0.3089 | 14.4 | 10500 | 0.3198 | 0.2169 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.11.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
|