File size: 1,994 Bytes
b619067 |
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 |
---
base_model: microsoft/wavlm-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavlm-base
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. -->
# wavlm-base
This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3321
- Accuracy: 0.8974
## 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: 8
- eval_batch_size: 2
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3744 | 1.0 | 793 | 0.3307 | 0.8974 |
| 0.3699 | 2.0 | 1586 | 0.3342 | 0.8974 |
| 0.2898 | 3.0 | 2379 | 0.3341 | 0.8974 |
| 0.3126 | 4.0 | 3173 | 0.3363 | 0.8974 |
| 0.3753 | 5.0 | 3966 | 0.3309 | 0.8974 |
| 0.3617 | 6.0 | 4759 | 0.3325 | 0.8974 |
| 0.3453 | 7.0 | 5552 | 0.3315 | 0.8974 |
| 0.3337 | 8.0 | 6346 | 0.3364 | 0.8974 |
| 0.2829 | 9.0 | 7139 | 0.3327 | 0.8974 |
| 0.3189 | 10.0 | 7930 | 0.3321 | 0.8974 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3
|