File size: 2,438 Bytes
af91175 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-child-en-tokenizer-4
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-child-en-tokenizer-4
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: 1.4709
- Wer: 0.3769
## 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: 0.0003
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0334 | 1.72 | 100 | 1.4709 | 0.3769 |
| 0.0332 | 3.45 | 200 | 1.4709 | 0.3769 |
| 0.0343 | 5.17 | 300 | 1.4709 | 0.3769 |
| 0.032 | 6.9 | 400 | 1.4709 | 0.3769 |
| 0.0332 | 8.62 | 500 | 1.4709 | 0.3769 |
| 0.0327 | 10.34 | 600 | 1.4709 | 0.3769 |
| 0.0331 | 12.07 | 700 | 1.4709 | 0.3769 |
| 0.0334 | 13.79 | 800 | 1.4709 | 0.3769 |
| 0.0319 | 15.52 | 900 | 1.4709 | 0.3769 |
| 0.0338 | 17.24 | 1000 | 1.4709 | 0.3769 |
| 0.0321 | 18.97 | 1100 | 1.4709 | 0.3769 |
| 0.0367 | 20.69 | 1200 | 1.4709 | 0.3769 |
| 0.0331 | 22.41 | 1300 | 1.4709 | 0.3769 |
| 0.0332 | 24.14 | 1400 | 1.4709 | 0.3769 |
| 0.0347 | 25.86 | 1500 | 1.4709 | 0.3769 |
| 0.0319 | 27.59 | 1600 | 1.4709 | 0.3769 |
| 0.0302 | 29.31 | 1700 | 1.4709 | 0.3769 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3
|