---
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_17
  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_17

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: 2.5577

## Model description

Trained on single ID token 5K dataset filtered to 10k sequences (30% for test data = 3000)

lora_alpha = 64 <--------------

lora_dropout = 0.1

lora_r = 128

epochs = 3

learning rate = 3e-4

warmup_steps=500

gradient_accumulation_steps = 1

train_batch = 2

eval_batch = 2

ALL Linear layers

Changed ' token to >     <--------------

## 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: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.7754        | 0.3749 | 1312  | 2.6704          |
| 2.6257        | 0.7497 | 2624  | 2.6140          |
| 2.576         | 1.1246 | 3936  | 2.5976          |
| 2.5475        | 1.4994 | 5248  | 2.5839          |
| 2.5424        | 1.8743 | 6560  | 2.5722          |
| 2.498         | 2.2491 | 7872  | 2.5708          |
| 2.4993        | 2.624  | 9184  | 2.5647          |
| 2.4939        | 2.9989 | 10496 | 2.5577          |


### Framework versions

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