File size: 1,479 Bytes
8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 3e31092 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad 8d9cf37 72147ad |
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 |
---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
base_model: NousResearch/Nous-Hermes-llama-2-7b
model-index:
- name: heading_investigation_e3
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. -->
# heading_investigation_e3
This model is a fine-tuned version of [NousResearch/Nous-Hermes-llama-2-7b](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2621
## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.7.1
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1 |