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---
base_model: facebook/wav2vec2-base-960h
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-960h-EMOPIA-10sec-full
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. -->
# wav2vec2-base-960h-EMOPIA-10sec-full
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2928
- Accuracy: 0.8488
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2057 | 1.0 | 2248 | 1.4522 | 0.4502 |
| 1.3873 | 2.0 | 4496 | 1.4503 | 0.6423 |
| 1.4246 | 3.0 | 6744 | 1.6165 | 0.6673 |
| 1.3335 | 4.0 | 8992 | 1.4786 | 0.7206 |
| 1.251 | 5.0 | 11240 | 1.6414 | 0.6886 |
| 1.1859 | 6.0 | 13488 | 1.3300 | 0.7544 |
| 1.1132 | 7.0 | 15736 | 1.3665 | 0.7509 |
| 1.0189 | 8.0 | 17984 | 1.6665 | 0.7153 |
| 0.9807 | 9.0 | 20232 | 1.1175 | 0.7794 |
| 0.8786 | 10.0 | 22480 | 1.1786 | 0.7883 |
| 0.8677 | 11.0 | 24728 | 1.1295 | 0.7811 |
| 0.7554 | 12.0 | 26976 | 1.1185 | 0.8185 |
| 0.7196 | 13.0 | 29224 | 1.4067 | 0.7847 |
| 0.692 | 14.0 | 31472 | 1.1175 | 0.8203 |
| 0.6276 | 15.0 | 33720 | 1.4490 | 0.7883 |
| 0.6083 | 16.0 | 35968 | 1.0983 | 0.8345 |
| 0.5204 | 17.0 | 38216 | 1.1814 | 0.8256 |
| 0.5197 | 18.0 | 40464 | 1.2945 | 0.8167 |
| 0.488 | 19.0 | 42712 | 1.4494 | 0.8025 |
| 0.4714 | 20.0 | 44960 | 1.3499 | 0.8114 |
| 0.3641 | 21.0 | 47208 | 1.2525 | 0.8381 |
| 0.3877 | 22.0 | 49456 | 1.2610 | 0.8381 |
| 0.3253 | 23.0 | 51704 | 1.3913 | 0.8274 |
| 0.2978 | 24.0 | 53952 | 1.2990 | 0.8416 |
| 0.3238 | 25.0 | 56200 | 1.4328 | 0.8274 |
| 0.2669 | 26.0 | 58448 | 1.3079 | 0.8327 |
| 0.2521 | 27.0 | 60696 | 1.3250 | 0.8399 |
| 0.2632 | 28.0 | 62944 | 1.3357 | 0.8416 |
| 0.2655 | 29.0 | 65192 | 1.2957 | 0.8434 |
| 0.2379 | 30.0 | 67440 | 1.2928 | 0.8488 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.0
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