---
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_15
  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_15

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: 2.5456

## Model description

Trained on single ID token 5K dataset filtered to 8k sequences

lora_alpha = 128

lora_dropout = 0.1

lora_r = 128

epochs = 3

learning rate = 3e-4

warmup_steps=200

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: 200
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.694         | 0.625 | 2500  | 2.5997          |
| 2.5703        | 1.25  | 5000  | 2.5697          |
| 2.5341        | 1.875 | 7500  | 2.5471          |
| 2.4969        | 2.5   | 10000 | 2.5456          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1