tensorboard safetensors generated_from_trainer base_model:Finnish-NLP/llama-7b-finnish-instruct-v0.2 base_model:finetune:Finnish-NLP/llama-7b-finnish-instruct-v0.2 license:apache-2.0 region:us
---
base_model: Finnish-NLP/llama-7b-finnish-instruct-v0.2
license: apache-2.0
metrics:
- accuracy
- bleu
- sacrebleu
- rouge
tags:
- generated_from_trainer
model-index:
- name: llama-7b-finnish-instruct-v0.2_En__translations_size_104_epochs_10_2024-06-22_03-40-15_3557998
  results: []
---

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# llama-7b-finnish-instruct-v0.2_En__translations_size_104_epochs_10_2024-06-22_03-40-15_3557998

This model is a fine-tuned version of [Finnish-NLP/llama-7b-finnish-instruct-v0.2](https://huggingface.co/Finnish-NLP/llama-7b-finnish-instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5080
- Accuracy: 0.574
- Chrf: 0.692
- Bleu: 0.544
- Sacrebleu: 0.5
- Rouge1: 0.598
- Rouge2: 0.374
- Rougel: 0.581
- Rougelsum: 0.585
- Meteor: 0.465

## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 3407
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 104
- training_steps: 1040

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf  | Bleu  | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|:------:|:------:|:---------:|:------:|
| 0.4205        | 4.0   | 104  | 1.0350          | 0.577    | 0.44  | 0.277 | 0.3       | 0.317  | 0.149  | 0.288  | 0.297     | 0.355  |
| 0.2068        | 8.0   | 208  | 0.9393          | 0.578    | 0.501 | 0.338 | 0.3       | 0.391  | 0.206  | 0.357  | 0.353     | 0.362  |
| 0.1289        | 12.0  | 312  | 0.8516          | 0.575    | 0.548 | 0.38  | 0.4       | 0.439  | 0.225  | 0.414  | 0.416     | 0.395  |
| 0.7509        | 16.0  | 416  | 0.7754          | 0.578    | 0.578 | 0.42  | 0.4       | 0.461  | 0.259  | 0.441  | 0.44      | 0.431  |
| 0.0951        | 20.0  | 520  | 0.7348          | 0.574    | 0.606 | 0.459 | 0.5       | 0.513  | 0.291  | 0.484  | 0.483     | 0.446  |
| 0.1201        | 24.0  | 624  | 0.6261          | 0.577    | 0.637 | 0.484 | 0.5       | 0.541  | 0.321  | 0.516  | 0.505     | 0.437  |
| 1.0287        | 28.0  | 728  | 0.5589          | 0.574    | 0.668 | 0.51  | 0.5       | 0.559  | 0.334  | 0.535  | 0.51      | 0.458  |
| 0.0522        | 32.0  | 832  | 0.5623          | 0.574    | 0.659 | 0.526 | 0.5       | 0.573  | 0.349  | 0.552  | 0.541     | 0.449  |
| 0.1314        | 36.0  | 936  | 0.5154          | 0.576    | 0.682 | 0.534 | 0.5       | 0.588  | 0.36   | 0.573  | 0.576     | 0.465  |
| 0.0449        | 40.0  | 1040 | 0.5080          | 0.574    | 0.692 | 0.544 | 0.5       | 0.598  | 0.374  | 0.581  | 0.585     | 0.465  |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.15.2
