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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: togethercomputer/evo-1-8k-base
model-index:
- name: lora_evo_ta_all_layers_13
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. -->
# lora_evo_ta_all_layers_13
This model is a fine-tuned version of [togethercomputer/evo-1-8k-base](https://huggingface.co/togethercomputer/evo-1-8k-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5250
## Model description
Trained on 1K dataset instead of 400
lora_alpha = 256
lora_dropout = 0.05
lora_r = 128
epochs = 3
learning rate = 3e-4
warmup_steps=100
gradient_accumulation_steps = 1
train_batch = 2
eval_batch = 2
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7264 | 1.0 | 1762 | 2.5781 |
| 2.5569 | 2.0 | 3524 | 2.5379 |
| 2.4982 | 3.0 | 5286 | 2.5250 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |