File size: 3,175 Bytes
53e29aa |
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 85 86 87 88 89 90 |
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-russian-demo-kaggle
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-russian-demo-kaggle
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.9997
## 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: 12
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0102 | 1.03 | 500 | inf | 0.9997 |
| 0.0068 | 2.06 | 1000 | inf | 0.9997 |
| 0.0 | 3.09 | 1500 | inf | 0.9997 |
| 0.0313 | 4.12 | 2000 | inf | 0.9997 |
| 0.0 | 5.15 | 2500 | inf | 0.9997 |
| 0.0052 | 6.19 | 3000 | inf | 0.9997 |
| 0.0287 | 7.22 | 3500 | inf | 0.9997 |
| 0.0 | 8.25 | 4000 | inf | 0.9997 |
| 0.01 | 9.28 | 4500 | inf | 0.9997 |
| 0.0 | 10.31 | 5000 | inf | 0.9997 |
| 0.3919 | 11.34 | 5500 | inf | 0.9997 |
| 0.0 | 12.37 | 6000 | inf | 0.9997 |
| 0.0 | 13.4 | 6500 | inf | 0.9997 |
| 0.0 | 14.43 | 7000 | inf | 0.9997 |
| 0.6422 | 15.46 | 7500 | inf | 0.9997 |
| 0.0 | 16.49 | 8000 | inf | 0.9997 |
| 0.0 | 17.53 | 8500 | inf | 0.9997 |
| 0.0 | 18.56 | 9000 | inf | 0.9997 |
| 0.0 | 19.59 | 9500 | inf | 0.9997 |
| 0.0 | 20.62 | 10000 | inf | 0.9997 |
| 0.0427 | 21.65 | 10500 | inf | 0.9997 |
| 0.0 | 22.68 | 11000 | inf | 0.9997 |
| 0.0 | 23.71 | 11500 | inf | 0.9997 |
| 0.0 | 24.74 | 12000 | inf | 0.9997 |
| 0.0091 | 25.77 | 12500 | inf | 0.9997 |
| 0.1243 | 26.8 | 13000 | inf | 0.9997 |
| 0.0 | 27.83 | 13500 | inf | 0.9997 |
| 0.0 | 28.87 | 14000 | inf | 0.9997 |
| 0.0 | 29.9 | 14500 | inf | 0.9997 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.9.1
- Datasets 1.13.3
- Tokenizers 0.10.3
|