File size: 2,961 Bytes
2cd1fe2 |
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 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
license: mit
base_model: HuggingFaceH4/zephyr-7b-beta
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-sft-lora-accum4-lr5e_5-dpo
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. -->
# zephyr-7b-sft-lora-accum4-lr5e_5-dpo
This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5041
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5276 | 0.55 | 13 | 1.4329 |
| 1.352 | 1.57 | 27 | 1.2406 |
| 1.1329 | 2.55 | 40 | 1.0909 |
| 1.0628 | 3.57 | 54 | 1.0299 |
| 1.0022 | 4.55 | 67 | 0.9812 |
| 0.957 | 5.57 | 81 | 0.9445 |
| 0.9148 | 6.55 | 94 | 0.8948 |
| 0.8443 | 7.57 | 108 | 0.8432 |
| 0.7645 | 8.55 | 121 | 0.7847 |
| 0.6952 | 9.57 | 135 | 0.7192 |
| 0.639 | 10.55 | 148 | 0.6671 |
| 0.5683 | 11.57 | 162 | 0.6112 |
| 0.5223 | 12.55 | 175 | 0.5777 |
| 0.4958 | 13.57 | 189 | 0.5592 |
| 0.4592 | 14.55 | 202 | 0.5381 |
| 0.4602 | 15.57 | 216 | 0.5100 |
| 0.4486 | 16.55 | 229 | 0.5117 |
| 0.4274 | 17.57 | 243 | 0.5084 |
| 0.4239 | 18.55 | 256 | 0.4909 |
| 0.4055 | 19.57 | 270 | 0.5006 |
| 0.3931 | 20.55 | 283 | 0.4959 |
| 0.3986 | 21.57 | 297 | 0.4853 |
| 0.3977 | 22.55 | 310 | 0.4859 |
| 0.3936 | 23.57 | 324 | 0.4974 |
| 0.3821 | 24.55 | 337 | 0.4952 |
| 0.3877 | 25.57 | 351 | 0.4949 |
| 0.3681 | 26.55 | 364 | 0.4866 |
| 0.3681 | 27.57 | 378 | 0.4926 |
| 0.371 | 28.55 | 391 | 0.4817 |
| 0.3604 | 29.57 | 405 | 0.4923 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|