metadata
library_name: peft
license: cc-by-nc-4.0
base_model: CohereLabs/aya-expanse-8b
tags:
- generated_from_trainer
datasets:
- matrixportal/turkish_medical_alpaca
model-index:
- name: outputs/lora-out
results: []
See axolotl config
axolotl version: 0.8.1
adapter: qlora
base_model: CohereLabs/aya-expanse-8b
bf16: auto
dataset_prepared_path: last_run_prepared
datasets:
- path: matrixportal/turkish_medical_alpaca
type: alpaca
debug: null
deepspeed: null
early_stopping_patience: null
eval_sample_packing: true
eval_table_size: null
evals_per_epoch: 1
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
learning_rate: 3e-5
load_in_4bit: true
load_in_8bit: false
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_modules_to_save:
- embed_tokens
- lm_head
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 50
micro_batch_size: 1
model_type: CohereForCausalLM
num_epochs: 1
optimizer: paged_adamw_8bit
output_dir: ./outputs/lora-out
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
saves_per_epoch: 1
sdp_attention: true
sequence_len: 2048
special_tokens:
bos_token: <BOS_TOKEN>
eos_token: <|END_OF_TURN_TOKEN|>
unk_token: <PAD>
strict: false
tf32: false
tokens:
- <|START_OF_TURN_TOKEN|>
- <|END_OF_TURN_TOKEN|>
train_on_inputs: false
val_set_size: 0.05
wandb_entity: matrixportalx-none
wandb_log_model: all
wandb_name: aya-turkish-medical
wandb_project: matrixportalx-none
wandb_watch: gradients
warmup_steps: 1
weight_decay: 0.0
xformers_attention: null
outputs/lora-out
This model is a fine-tuned version of CohereLabs/aya-expanse-8b on the matrixportal/turkish_medical_alpaca dataset. It achieves the following results on the evaluation set:
- Loss: 6.7830
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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2
- training_steps: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.0385 | 0.0172 | 50 | 6.7830 |
Framework versions
- PEFT 0.15.1
- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1