metadata
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-1B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: llama-1b-irony
results: []
llama-1b-irony
This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6571
- Accuracy: 0.6658
- F1: 0.5112
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 30 | 0.8135 | 0.6441 | 0.5114 |
| No log | 2.0 | 60 | 0.7566 | 0.6122 | 0.5529 |
| No log | 3.0 | 90 | 0.7246 | 0.6301 | 0.5338 |
| No log | 4.0 | 120 | 0.6850 | 0.6467 | 0.5249 |
| No log | 5.0 | 150 | 0.6739 | 0.6722 | 0.5353 |
| No log | 6.0 | 180 | 0.6852 | 0.6556 | 0.4706 |
| No log | 7.0 | 210 | 0.6446 | 0.6862 | 0.5669 |
| No log | 8.0 | 240 | 0.6489 | 0.6747 | 0.5487 |
| No log | 9.0 | 270 | 0.6449 | 0.6747 | 0.5422 |
| No log | 10.0 | 300 | 0.6571 | 0.6658 | 0.5112 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0