File size: 1,904 Bytes
2b28e0c 0023202 2b28e0c |
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 |
---
license: apache-2.0
base_model: teknium/OpenHermes-2.5-Mistral-7B
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: criticon-sft-v0.1
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. -->
# criticon-sft-v0.1
This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4668
## WandB logs
- [criticon logs](https://wandb.ai/argilla-io/criticon/runs/g8sd5jhi?nw=nwuserplagussargilla)
## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6226 | 0.29 | 500 | 0.6215 |
| 0.5616 | 0.57 | 1000 | 0.5684 |
| 0.5384 | 0.86 | 1500 | 0.5288 |
| 0.4248 | 1.14 | 2000 | 0.5098 |
| 0.3969 | 1.43 | 2500 | 0.4809 |
| 0.3933 | 1.72 | 3000 | 0.4668 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
|