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---
base_model: unsloth/Qwen2-7B
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Qwen2-7B_pct_default_r16
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. -->
# Qwen2-7B_pct_default_r16
This model is a fine-tuned version of [unsloth/Qwen2-7B](https://huggingface.co./unsloth/Qwen2-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9141
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.031 | 0.0206 | 8 | 1.9518 |
| 2.0039 | 0.0412 | 16 | 1.9527 |
| 2.0258 | 0.0618 | 24 | 1.9364 |
| 1.9476 | 0.0824 | 32 | 1.9396 |
| 1.993 | 0.1031 | 40 | 1.9391 |
| 1.9924 | 0.1237 | 48 | 1.9413 |
| 2.0036 | 0.1443 | 56 | 1.9407 |
| 1.9358 | 0.1649 | 64 | 1.9378 |
| 1.9956 | 0.1855 | 72 | 1.9401 |
| 2.0183 | 0.2061 | 80 | 1.9399 |
| 1.9952 | 0.2267 | 88 | 1.9411 |
| 1.9309 | 0.2473 | 96 | 1.9413 |
| 2.0042 | 0.2680 | 104 | 1.9426 |
| 1.8885 | 0.2886 | 112 | 1.9405 |
| 1.9462 | 0.3092 | 120 | 1.9409 |
| 1.9787 | 0.3298 | 128 | 1.9441 |
| 1.9647 | 0.3504 | 136 | 1.9408 |
| 1.9391 | 0.3710 | 144 | 1.9398 |
| 2.0038 | 0.3916 | 152 | 1.9389 |
| 2.0412 | 0.4122 | 160 | 1.9402 |
| 2.0523 | 0.4329 | 168 | 1.9371 |
| 1.9364 | 0.4535 | 176 | 1.9394 |
| 1.9805 | 0.4741 | 184 | 1.9395 |
| 1.9935 | 0.4947 | 192 | 1.9380 |
| 1.9342 | 0.5153 | 200 | 1.9346 |
| 1.9708 | 0.5359 | 208 | 1.9361 |
| 2.0128 | 0.5565 | 216 | 1.9355 |
| 1.9416 | 0.5771 | 224 | 1.9304 |
| 1.9658 | 0.5977 | 232 | 1.9349 |
| 1.9161 | 0.6184 | 240 | 1.9258 |
| 1.94 | 0.6390 | 248 | 1.9258 |
| 1.9908 | 0.6596 | 256 | 1.9244 |
| 1.9169 | 0.6802 | 264 | 1.9242 |
| 1.9868 | 0.7008 | 272 | 1.9216 |
| 1.8737 | 0.7214 | 280 | 1.9209 |
| 2.0166 | 0.7420 | 288 | 1.9198 |
| 1.9246 | 0.7626 | 296 | 1.9188 |
| 1.9418 | 0.7833 | 304 | 1.9198 |
| 1.9417 | 0.8039 | 312 | 1.9172 |
| 1.9652 | 0.8245 | 320 | 1.9169 |
| 1.9715 | 0.8451 | 328 | 1.9171 |
| 1.9634 | 0.8657 | 336 | 1.9159 |
| 1.9566 | 0.8863 | 344 | 1.9153 |
| 1.9277 | 0.9069 | 352 | 1.9147 |
| 2.0087 | 0.9275 | 360 | 1.9142 |
| 1.921 | 0.9481 | 368 | 1.9143 |
| 1.9842 | 0.9688 | 376 | 1.9140 |
| 1.8825 | 0.9894 | 384 | 1.9141 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |