metadata
base_model: google/gemma-2-2b-it
library_name: peft
license: gemma
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: PaperPrism_gemma2
results: []
PaperPrism_gemma2
This model is a fine-tuned version of google/gemma-2-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2055
- Accuracy: 0.7476
- F1: 0.7142
- Precision: 0.7845
- Recall: 0.7476
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 0.0300 | 100 | 1.5942 | 0.7248 | 0.7061 | 0.7081 | 0.7248 |
| No log | 0.0601 | 200 | 1.6005 | 0.7524 | 0.7241 | 0.7486 | 0.7524 |
| No log | 0.0901 | 300 | 1.4531 | 0.7656 | 0.7506 | 0.7555 | 0.7656 |
| No log | 0.1202 | 400 | 1.8157 | 0.7332 | 0.7134 | 0.7484 | 0.7332 |
| 0.591 | 0.1502 | 500 | 1.4562 | 0.7825 | 0.7753 | 0.7774 | 0.7825 |
| 0.591 | 0.1803 | 600 | 1.3786 | 0.7692 | 0.7636 | 0.7816 | 0.7692 |
| 0.591 | 0.2103 | 700 | 2.2055 | 0.7476 | 0.7142 | 0.7845 | 0.7476 |
Framework versions
- PEFT 0.13.0
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0