File size: 2,651 Bytes
195d59f 3d71397 195d59f 3d71397 195d59f 3d71397 195d59f 3d71397 195d59f 3d71397 195d59f 3d71397 195d59f |
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
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Osiris_asr_model
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. -->
# Osiris_asr_model
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: 3.0600
- Wer: 1.0
## 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: 1e-05
- train_batch_size: 10
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 45.8209 | 50.0 | 50 | 21.0347 | 1.0182 |
| 10.2898 | 100.0 | 100 | 5.1552 | 1.0 |
| 5.7188 | 150.0 | 150 | 4.9140 | 1.0 |
| 5.3358 | 200.0 | 200 | 4.7650 | 1.0 |
| 5.1381 | 250.0 | 250 | 4.6797 | 1.0 |
| 4.9841 | 300.0 | 300 | 4.6168 | 1.0 |
| 4.9255 | 350.0 | 350 | 4.5741 | 1.0 |
| 4.8353 | 400.0 | 400 | 4.5321 | 1.0 |
| 4.7704 | 450.0 | 450 | 4.5100 | 1.0 |
| 4.6257 | 500.0 | 500 | 3.9382 | 1.0 |
| 3.8106 | 550.0 | 550 | 3.3939 | 1.0 |
| 3.5095 | 600.0 | 600 | 3.2887 | 1.0 |
| 3.3716 | 650.0 | 650 | 3.1967 | 1.0 |
| 3.3025 | 700.0 | 700 | 3.1539 | 1.0 |
| 3.2532 | 750.0 | 750 | 3.1477 | 1.0 |
| 3.2086 | 800.0 | 800 | 3.0984 | 1.0 |
| 3.1889 | 850.0 | 850 | 3.0857 | 1.0 |
| 3.162 | 900.0 | 900 | 3.0819 | 1.0 |
| 3.1411 | 950.0 | 950 | 3.0610 | 1.0 |
| 3.1397 | 1000.0 | 1000 | 3.0600 | 1.0 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|