File size: 2,367 Bytes
46b4ff0 |
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_at0.0_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_at0.0_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: 1.0838
- Wer: 0.1768
## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.3345 | 3.91 | 250 | 3.9551 | 1.0 |
| 3.2558 | 7.81 | 500 | 3.1516 | 1.0 |
| 2.9971 | 11.72 | 750 | 2.4403 | 1.0 |
| 0.9923 | 15.62 | 1000 | 0.6040 | 0.4938 |
| 0.2971 | 19.53 | 1250 | 0.6870 | 0.2828 |
| 0.1765 | 23.44 | 1500 | 0.8956 | 0.2431 |
| 0.1185 | 27.34 | 1750 | 0.9472 | 0.2029 |
| 0.0919 | 31.25 | 2000 | 1.0306 | 0.1833 |
| 0.0692 | 35.16 | 2250 | 0.9844 | 0.1939 |
| 0.0577 | 39.06 | 2500 | 1.0122 | 0.1862 |
| 0.0467 | 42.97 | 2750 | 1.0849 | 0.1734 |
| 0.0407 | 46.88 | 3000 | 0.9989 | 0.1841 |
| 0.0341 | 50.78 | 3250 | 1.0820 | 0.1875 |
| 0.0299 | 54.69 | 3500 | 1.1344 | 0.1747 |
| 0.0291 | 58.59 | 3750 | 1.0495 | 0.1845 |
| 0.0247 | 62.5 | 4000 | 1.0838 | 0.1768 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|