TempReason-L1
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the EllieS/TempReason-L1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2934
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: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2862 | 1.0 | 25000 | 0.2934 |
Framework versions
- PEFT 0.7.1
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for EllieS/TempReason-L1
Base model
mistralai/Mistral-7B-v0.1 Finetuned
alignment-handbook/zephyr-7b-sft-full
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("alignment-handbook/zephyr-7b-sft-full") model = PeftModel.from_pretrained(base_model, "EllieS/TempReason-L1")