File size: 2,176 Bytes
99d6d7b |
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-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
metrics:
- wer
model-index:
- name: enko_xlsr_13p_run1
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. -->
# enko_xlsr_13p_run1
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3042
- Wer: 0.1696
## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.6595 | 1.0 | 7702 | 0.4495 | 0.2974 |
| 0.5717 | 2.0 | 15404 | 0.3982 | 0.2562 |
| 0.5134 | 3.0 | 23106 | 0.3769 | 0.2365 |
| 0.467 | 4.0 | 30808 | 0.3499 | 0.2203 |
| 0.4156 | 5.0 | 38510 | 0.3391 | 0.2116 |
| 0.379 | 6.0 | 46212 | 0.3327 | 0.1999 |
| 0.3475 | 7.0 | 53914 | 0.3127 | 0.1947 |
| 0.3105 | 8.0 | 61616 | 0.3081 | 0.1814 |
| 0.281 | 9.0 | 69318 | 0.3068 | 0.1742 |
| 0.2584 | 10.0 | 77020 | 0.3040 | 0.1713 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
|