peft safetensors generated_from_trainer base_model:dominguesm/canarim-7b-instruct license:llama2 region:us
---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: dominguesm/canarim-7b-instruct
model-index:
- name: themis-instruct
  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. -->

# themis-instruct

This model is a fine-tuned version of [dominguesm/canarim-7b-instruct](https://huggingface.co/dominguesm/canarim-7b-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8855

## 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: 2.5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0042        | 0.03  | 25   | 1.3872          |
| 1.2414        | 0.05  | 50   | 1.1247          |
| 1.0936        | 0.08  | 75   | 1.0210          |
| 1.0607        | 0.11  | 100  | 0.9881          |
| 1.0186        | 0.13  | 125  | 0.9693          |
| 0.9851        | 0.16  | 150  | 0.9552          |
| 1.0123        | 0.18  | 175  | 0.9469          |
| 0.9737        | 0.21  | 200  | 0.9398          |
| 0.9408        | 0.24  | 225  | 0.9371          |
| 0.9129        | 0.26  | 250  | 0.9300          |
| 0.9441        | 0.29  | 275  | 0.9254          |
| 0.9577        | 0.32  | 300  | 0.9198          |
| 0.9509        | 0.34  | 325  | 0.9162          |
| 0.9023        | 0.37  | 350  | 0.9135          |
| 0.8924        | 0.4   | 375  | 0.9109          |
| 0.9207        | 0.42  | 400  | 0.9086          |
| 0.9436        | 0.45  | 425  | 0.9058          |
| 0.8637        | 0.47  | 450  | 0.9047          |
| 0.9207        | 0.5   | 475  | 0.9033          |
| 0.9475        | 0.53  | 500  | 0.9002          |
| 0.9548        | 0.55  | 525  | 0.8981          |
| 0.8806        | 0.58  | 550  | 0.8969          |
| 0.9475        | 0.61  | 575  | 0.8949          |
| 0.8505        | 0.63  | 600  | 0.8932          |
| 0.8999        | 0.66  | 625  | 0.8926          |
| 0.9018        | 0.68  | 650  | 0.8906          |
| 0.9107        | 0.71  | 675  | 0.8901          |
| 0.8557        | 0.74  | 700  | 0.8888          |
| 0.8903        | 0.76  | 725  | 0.8881          |
| 0.8718        | 0.79  | 750  | 0.8875          |
| 0.9002        | 0.82  | 775  | 0.8870          |
| 0.9086        | 0.84  | 800  | 0.8867          |
| 0.8983        | 0.87  | 825  | 0.8863          |
| 0.9401        | 0.9   | 850  | 0.8861          |
| 0.9434        | 0.92  | 875  | 0.8857          |
| 0.8987        | 0.95  | 900  | 0.8855          |
| 0.9008        | 0.97  | 925  | 0.8855          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0