File size: 2,052 Bytes
f2cc44a |
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 |
---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-0.5B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: reranker_continuous_filt_max7_train
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. -->
# reranker_continuous_filt_max7_train
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co./Qwen/Qwen2.5-0.5B-Instruct) on the reranker_continuous_filt_max7_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3869
## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.403 | 0.1000 | 1977 | 0.4783 |
| 0.5192 | 0.2000 | 3954 | 0.4524 |
| 0.3639 | 0.3000 | 5931 | 0.4370 |
| 0.4343 | 0.4000 | 7908 | 0.4286 |
| 0.3929 | 0.5000 | 9885 | 0.4163 |
| 0.4455 | 0.6000 | 11862 | 0.4040 |
| 0.3775 | 0.7000 | 13839 | 0.3947 |
| 0.3629 | 0.8000 | 15816 | 0.3898 |
| 0.5186 | 0.9000 | 17793 | 0.3872 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|