---
base_model: ybelkada/falcon-7b-sharded-bf16
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: falcon-7b-sharded-bf16-finetuned-html-code-generation
  results: []
---

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# falcon-7b-sharded-bf16-finetuned-html-code-generation

This model is a fine-tuned version of [ybelkada/falcon-7b-sharded-bf16](https://huggingface.co/ybelkada/falcon-7b-sharded-bf16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7291

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 320

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.1794 | 20   | 1.8065          |
| No log        | 0.3587 | 40   | 1.4784          |
| No log        | 0.5381 | 60   | 1.3639          |
| No log        | 0.7175 | 80   | 1.2722          |
| No log        | 0.8969 | 100  | 1.2048          |
| No log        | 1.0762 | 120  | 1.1346          |
| No log        | 1.2556 | 140  | 1.1228          |
| No log        | 1.4350 | 160  | 1.0076          |
| No log        | 1.6143 | 180  | 0.9714          |
| No log        | 1.7937 | 200  | 0.9035          |
| No log        | 1.9731 | 220  | 0.8549          |
| No log        | 2.1525 | 240  | 0.7914          |
| No log        | 2.3318 | 260  | 0.7572          |
| No log        | 2.5112 | 280  | 0.7365          |
| No log        | 2.6906 | 300  | 0.7301          |
| No log        | 2.8700 | 320  | 0.7291          |


### Framework versions

- PEFT 0.11.2.dev0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1