File size: 1,914 Bytes
e08c7ca ada9d9b e08c7ca ada9d9b e08c7ca |
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 |
---
library_name: peft
license: bigscience-bloom-rail-1.0
base_model: bigscience/bloomz-3b
tags:
- generated_from_trainer
model-index:
- name: bloomz_lora_mn
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bilegjargal-minerva-university/capstone-dense-seq/runs/nnw937sn)
# bloomz_lora_mn
This model is a fine-tuned version of [bigscience/bloomz-3b](https://huggingface.co/bigscience/bloomz-3b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4090
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.938 | 0.1820 | 1000 | 2.9015 |
| 2.6901 | 0.3641 | 2000 | 2.7353 |
| 2.5543 | 0.5461 | 3000 | 2.5426 |
| 2.4624 | 0.7282 | 4000 | 2.4493 |
| 2.4762 | 0.9102 | 5000 | 2.4090 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.45.0
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3 |