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pedromatias97/
little-llama2-ft-qa

Name: little-llama2-ft-qa
Availability: InStock

peft

tensorboard

safetensors

generated_from_trainer

TinyLlama/TinyLlama-1.1B-Chat-v1.0

adapter

apache-2.0

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little-llama2-ft-qa

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.5732

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

The following bitsandbytes quantization config was used during training:

quant_method: bitsandbytes
_load_in_8bit: False
_load_in_4bit: True
llm_int8_threshold: 6.0
llm_int8_skip_modules: None
llm_int8_enable_fp32_cpu_offload: False
llm_int8_has_fp16_weight: False
bnb_4bit_quant_type: nf4
bnb_4bit_use_double_quant: False
bnb_4bit_compute_dtype: float16
load_in_4bit: True
load_in_8bit: False

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.2789	0.2	250	1.5908
0.9655	0.4	500	1.5828
0.9788	0.6	750	1.5764
1.3064	0.8	1000	1.5739
1.0251	1.0	1250	1.5732

Inference

python

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

# prompt template
def generate_inference_prompt(context, question):
    return f"""### Instruction: Please answer to the question based on the context information provided. If you don't know the answer, please just say you don't know it, don't try to make an answer from that.\n
            ### Context:
            {context.strip()}\n

            ### Question:
            {question.strip()}

            ### Answer:
            
            """.strip()

# context to answer
context = """
Great Britain (commonly shortened to Britain) is an island in the North Atlantic Ocean off the north-west coast of continental Europe, consisting of England, Scotland and Wales. With an area of 209,331 km2 (80,823 sq mi), it is the largest of the British Isles, the largest European island and the ninth-largest island in the world. It is dominated by a maritime climate with narrow temperature differences between seasons. The island of Ireland, with an area 40 per cent that of Great Britain, is to the west—these islands, along with over 1,000 smaller surrounding islands and named substantial rocks, form the British Isles archipelago.
"""

# question to ask
question = """
What is the % of area occupied by Ireland in Great Britain?
"""

# loading model
model = AutoModelForCausalLM.from_pretrained(
'pedromatias97/little-llama2-ft-qa'
)

# load tokenizer
tokenizer = AutoTokenizer.from_pretrained(
'pedromatias97/little-llama2-ft-qa'
)

# pipeline
pipe = pipeline(
    "text-generation", 
    model=model, 
    tokenizer = tokenizer, 
    torch_dtype=torch.bfloat16, 
    device_map="auto"
)

# generate prompt
prompt = generate_inference_prompt(context, question)

# generate text
sequences = pipe(
    prompt,
    do_sample=True,
    max_new_tokens=10, 
    temperature=0.7, 
    top_k=50, 
    top_p=0.95,
    num_return_sequences=1,
)

# print result
print(sequences[0]['generated_text'])

### output: 40 per cent that of Great Britain

Framework versions

PEFT 0.5.0
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.15.2