---
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_5
  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_5

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: 2.9413

## Model description

Maybe the best one:

lora_alpha = 32

lora_dropout = 0.05

lora_r = 16

epochs = 3

learning rate = 3e-4

warmup_steps=85 <-------

gradient_accumulation_steps = 8

train_batch = 1

eval_batch = 1


## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 85
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.0785        | 0.9925 | 33   | 2.9956          |
| 2.9204        | 1.9850 | 66   | 2.9531          |
| 2.7515        | 2.9774 | 99   | 2.9413          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1