File size: 4,861 Bytes
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library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: tiny-audio-embedded
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. -->
# tiny-audio-embedded
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2044
## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2000
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.9934 | 0.0153 | 1000 | 0.3840 |
| 0.9974 | 0.0306 | 2000 | 0.4156 |
| 1.0350 | 0.0459 | 3000 | 0.3944 |
| 0.9922 | 0.0612 | 4000 | 0.3625 |
| 1.0129 | 0.0765 | 5000 | 0.3386 |
| 0.8650 | 0.0918 | 6000 | 0.3348 |
| 0.9696 | 0.1071 | 7000 | 0.3241 |
| 0.9879 | 0.1224 | 8000 | 0.3174 |
| 0.9225 | 0.1377 | 9000 | 0.3154 |
| 0.8560 | 0.1530 | 10000 | 0.3139 |
| 0.8554 | 0.1683 | 11000 | 0.3062 |
| 0.9126 | 0.1836 | 12000 | 0.3000 |
| 0.9142 | 0.1989 | 13000 | 0.2994 |
| 0.8358 | 0.2142 | 14000 | 0.2943 |
| 0.8452 | 0.2295 | 15000 | 0.2916 |
| 0.8372 | 0.2449 | 16000 | 0.2822 |
| 0.8776 | 0.2602 | 17000 | 0.2783 |
| 0.8697 | 0.2755 | 18000 | 0.2809 |
| 0.8541 | 0.2908 | 19000 | 0.2765 |
| 0.8511 | 0.3061 | 20000 | 0.2728 |
| 0.8440 | 0.3214 | 21000 | 0.2739 |
| 0.7897 | 0.3367 | 22000 | 0.2648 |
| 0.8196 | 0.3520 | 23000 | 0.2608 |
| 0.8320 | 0.3673 | 24000 | 0.2614 |
| 0.8043 | 0.3826 | 25000 | 0.2636 |
| 0.7875 | 0.3979 | 26000 | 0.2551 |
| 0.8257 | 0.4132 | 27000 | 0.2501 |
| 0.7276 | 0.4285 | 28000 | 0.2519 |
| 0.8196 | 0.4438 | 29000 | 0.2482 |
| 0.7727 | 0.4591 | 30000 | 0.2497 |
| 0.8316 | 0.4744 | 31000 | 0.2467 |
| 0.7738 | 0.4897 | 32000 | 0.2404 |
| 0.8146 | 0.5050 | 33000 | 0.2410 |
| 0.7571 | 0.5203 | 34000 | 0.2370 |
| 0.7921 | 0.5356 | 35000 | 0.2344 |
| 0.7792 | 0.5509 | 36000 | 0.2319 |
| 0.7014 | 0.5662 | 37000 | 0.2322 |
| 0.7425 | 0.5815 | 38000 | 0.2281 |
| 0.7644 | 0.5968 | 39000 | 0.2265 |
| 0.7048 | 0.6121 | 40000 | 0.2251 |
| 0.6970 | 0.6274 | 41000 | 0.2229 |
| 0.7856 | 0.6427 | 42000 | 0.2214 |
| 0.7114 | 0.6580 | 43000 | 0.2194 |
| 0.7751 | 0.6733 | 44000 | 0.2183 |
| 0.6482 | 0.6886 | 45000 | 0.2169 |
| 0.6889 | 0.7040 | 46000 | 0.2154 |
| 0.7554 | 0.7193 | 47000 | 0.2147 |
| 0.7050 | 0.7346 | 48000 | 0.2124 |
| 0.7927 | 0.7499 | 49000 | 0.2118 |
| 0.7309 | 0.7652 | 50000 | 0.2108 |
| 0.7264 | 0.7805 | 51000 | 0.2108 |
| 0.7256 | 0.7958 | 52000 | 0.2087 |
| 0.7605 | 0.8111 | 53000 | 0.2078 |
| 0.7391 | 0.8264 | 54000 | 0.2082 |
| 0.6781 | 0.8417 | 55000 | 0.2065 |
| 0.7206 | 0.8570 | 56000 | 0.2060 |
| 0.7342 | 0.8723 | 57000 | 0.2051 |
| 0.7519 | 0.8876 | 58000 | 0.2055 |
| 0.7258 | 0.9029 | 59000 | 0.2051 |
| 0.7932 | 0.9182 | 60000 | 0.2047 |
| 0.7391 | 0.9335 | 61000 | 0.2047 |
| 0.7416 | 0.9488 | 62000 | 0.2046 |
| 0.7249 | 0.9641 | 63000 | 0.2045 |
| 0.7000 | 0.9794 | 64000 | 0.2044 |
| 0.6958 | 0.9947 | 65000 | 0.2044 |
| 0.6692 | 1.0 | 65346 | 0.2044 |
### Framework versions
- Transformers 5.7.0
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2
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