File size: 2,203 Bytes
9541b4b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
---
base_model: google/gemma-2-2b-it
library_name: peft
license: gemma
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-2_60-samples_config-1_auto
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. -->
# Gemma-2-2B_task-2_60-samples_config-1_auto
This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co./google/gemma-2-2b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5317
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.9547 | 0.8696 | 5 | 1.0680 |
| 0.9627 | 1.9130 | 11 | 0.9490 |
| 0.7983 | 2.9565 | 17 | 0.8335 |
| 0.6484 | 4.0 | 23 | 0.7681 |
| 0.5716 | 4.8696 | 28 | 0.7258 |
| 0.5093 | 5.9130 | 34 | 0.6977 |
| 0.4159 | 6.9565 | 40 | 0.6919 |
| 0.358 | 8.0 | 46 | 0.7207 |
| 0.304 | 8.8696 | 51 | 0.7752 |
| 0.2095 | 9.9130 | 57 | 0.9146 |
| 0.1363 | 10.9565 | 63 | 1.0754 |
| 0.0658 | 12.0 | 69 | 1.2561 |
| 0.0395 | 12.8696 | 74 | 1.4315 |
| 0.0209 | 13.9130 | 80 | 1.5317 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |