metadata
license: gemma
base_model: google/gemma-7b
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- masakhane/african-ultrachat
model-index:
- name: zephyr-7b-gemma-sft-african-ultrachat
results: []
zephyr-7b-gemma-sft-african-ultrachat
This model is a fine-tuned version of google/gemma-7b on the masakhane/african-ultrachat dataset. It achieves the following results on the evaluation set:
- Loss: 1.0802
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.1942 | 1.0 | 2089 | 1.1757 |
0.952 | 2.0 | 4178 | 1.0642 |
0.7033 | 3.0 | 6267 | 1.0802 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
How to use
import torch
from transformers import pipeline
pipe = pipeline("text-generation", model="masakhane/zephyr-7b-gemma-sft-african-ultrachat", torch_dtype=torch.bfloat16, device_map="auto")
# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
messages = [
{
"role": "system",
"content": "You are a friendly chatbot who always responds in the style of a pirate",
},
{"role": "user", "content": "α°αα α₯αα΄α΅ αα
?"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
# <|system|>
# You are a friendly chatbot who always responds in the style of a pirate<eos>
# <|user|>
# α°αα α₯αα΄α΅ αα
?<eos>
# <|assistant|>
# α°αα α₯αα΄α΅ αα
/αα½? α₯αα α α€α ααα’ α₯αα°αα αα
/αα½ α₯α α¨αα΅αααα α₯αα΄α΅ αα?