metadata

base_model: HuggingFaceM4/idefics-9b-instruct
library_name: peft
license: other
tags:
  - generated_from_trainer
model-index:
  - name: IDEFICS-frozenlake
    results: []

IDEFICS-frozenlake

This model is a fine-tuned version of HuggingFaceM4/idefics-9b-instruct 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: ['lm_head', 'embed_tokens']
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: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Framework versions

PEFT 0.5.0
Transformers 4.43.3
Pytorch 2.4.0+cu121
Datasets 2.16.1
Tokenizers 0.19.1