README.md

metadata

library_name: peft
base_model: ybelkada/falcon-7b-sharded-bf16
tags:
  - trl
  - sft
  - generated_from_trainer
  - falcon
  - mental health
  - chatbot
model-index:
  - name: falcon-7b-sharded-bf16-finetuned-mental-health-conv
    results: []
license: mit
datasets:
  - heliosbrahma/mental_health_chatbot_dataset
language:
  - en
pipeline_tag: question-answering

falcon-7b-sharded-bf16-finetuned-mental-health-conv

This model is a fine-tuned version of ybelkada/falcon-7b-sharded-bf16 on an unknown dataset.

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: True
• bnb_4bit_compute_dtype: bfloat16
• bnb_4bit_quant_storage: uint8
• load_in_4bit: True
• load_in_8bit: False

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• training_steps: 100

Training results

Framework versions

• PEFT 0.5.0
• Transformers 4.44.2
• Pytorch 2.4.0
• Datasets 2.16.0
• Tokenizers 0.19.1