File size: 2,336 Bytes
da250ea |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_wav2vec2.0-base-on-IEMOCAP_2
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. -->
# finetuned_wav2vec2.0-base-on-IEMOCAP_2
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1569
- Accuracy: 0.7390
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1881 | 0.99 | 112 | 1.2005 | 0.4768 |
| 1.0121 | 2.0 | 225 | 1.0271 | 0.5619 |
| 0.8569 | 3.0 | 338 | 0.9382 | 0.6018 |
| 0.8679 | 4.0 | 451 | 0.8015 | 0.6947 |
| 0.5643 | 4.99 | 563 | 0.7752 | 0.7046 |
| 0.4579 | 6.0 | 676 | 0.7699 | 0.7400 |
| 0.3993 | 7.0 | 789 | 0.8323 | 0.7102 |
| 0.319 | 8.0 | 902 | 0.7763 | 0.7400 |
| 0.1876 | 8.99 | 1014 | 0.8912 | 0.7334 |
| 0.1888 | 10.0 | 1127 | 0.8836 | 0.7312 |
| 0.1526 | 11.0 | 1240 | 1.0474 | 0.7290 |
| 0.0451 | 12.0 | 1353 | 1.0455 | 0.7434 |
| 0.1281 | 12.99 | 1465 | 1.1207 | 0.7412 |
| 0.0363 | 14.0 | 1578 | 1.1232 | 0.7445 |
| 0.0512 | 14.9 | 1680 | 1.1217 | 0.7412 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3
|