See axolotl config
axolotl version: 0.4.0
base_model: meta-llama/Llama-2-7b-hf
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
tokenizer_config: meta-llama/Llama-2-7b-hf
is_llama_derived_model: true
load_in_8bit: true
load_in_4bit: false
strict: false
datasets:
- path: Cognitive-Lab/Kannada_Bilingual_Instruct
type: completion
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./kannada_out_peft_instruct_final_no_ext
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
adapter: lora
lora_model_dir:
lora_r: 256
lora_alpha: 128
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project: Ambari-Instruct-No-Extension
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 14
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 1
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 10
debug:
# deepspeed: deepspeed/zero2.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
kannada_out_peft_instruct_final_no_ext
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4334
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: 14
- eval_batch_size: 14
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 112
- total_eval_batch_size: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.3109 | 1.0 | 888 | 0.4334 |
Framework versions
- PEFT 0.9.0
- Transformers 4.40.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0
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Model tree for CognitiveLab/Ambari-One-Thrid-PEFT_final
Base model
meta-llama/Llama-2-7b-hf
Adapter
this model