mikhail-panzo's picture
End of training
2831b6f verified
|
raw
history blame
No virus
2.3 kB
---
license: mit
base_model: mikhail-panzo/zlm_b64_le4_s12000
tags:
- generated_from_trainer
model-index:
- name: zlm-fil_b64_le5_s8000
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. -->
# zlm-fil_b64_le5_s8000
This model is a fine-tuned version of [mikhail-panzo/zlm_b64_le4_s12000](https://huggingface.co/mikhail-panzo/zlm_b64_le4_s12000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4118
## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 8000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.5529 | 22.2222 | 500 | 0.5000 |
| 0.4974 | 44.4444 | 1000 | 0.4557 |
| 0.4716 | 66.6667 | 1500 | 0.4359 |
| 0.453 | 88.8889 | 2000 | 0.4246 |
| 0.4428 | 111.1111 | 2500 | 0.4196 |
| 0.4332 | 133.3333 | 3000 | 0.4171 |
| 0.4246 | 155.5556 | 3500 | 0.4154 |
| 0.4202 | 177.7778 | 4000 | 0.4133 |
| 0.4223 | 200.0 | 4500 | 0.4145 |
| 0.4127 | 222.2222 | 5000 | 0.4118 |
| 0.418 | 244.4444 | 5500 | 0.4130 |
| 0.4137 | 266.6667 | 6000 | 0.4130 |
| 0.4105 | 288.8889 | 6500 | 0.4127 |
| 0.4164 | 311.1111 | 7000 | 0.4127 |
| 0.4088 | 333.3333 | 7500 | 0.4120 |
| 0.4028 | 355.5556 | 8000 | 0.4118 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1