File size: 2,368 Bytes
808f867 bd064d3 808f867 bd064d3 808f867 bd064d3 808f867 |
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
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.4_da1
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. -->
# w2v2-base-pretrained_lr5e-5_at0.4_da1
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: 1.4372
- Wer: 0.1666
## 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: 32
- 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
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.4042 | 4.03 | 250 | 4.2497 | 1.0 |
| 3.3741 | 8.06 | 500 | 3.2004 | 1.0 |
| 3.1004 | 12.1 | 750 | 3.1159 | 1.0 |
| 2.3298 | 16.13 | 1000 | 1.0486 | 0.7809 |
| 0.5044 | 20.16 | 1250 | 0.6083 | 0.3464 |
| 0.27 | 24.19 | 1500 | 0.6948 | 0.2456 |
| 0.1833 | 28.23 | 1750 | 0.9908 | 0.1956 |
| 0.1324 | 32.26 | 2000 | 1.0134 | 0.1995 |
| 0.1027 | 36.29 | 2250 | 1.3176 | 0.1760 |
| 0.0852 | 40.32 | 2500 | 1.1929 | 0.1837 |
| 0.0703 | 44.35 | 2750 | 1.3824 | 0.1670 |
| 0.0601 | 48.39 | 3000 | 1.3337 | 0.1674 |
| 0.0546 | 52.42 | 3250 | 1.3566 | 0.1717 |
| 0.05 | 56.45 | 3500 | 1.4653 | 0.1670 |
| 0.046 | 60.48 | 3750 | 1.4321 | 0.1696 |
| 0.0452 | 64.52 | 4000 | 1.4372 | 0.1666 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|