metadata
license: other
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: google/gemma-2b
model-index:
- name: gemma_odia_2b
results: []
See axolotl config
axolotl version: 0.4.0
# use google/gemma-7b if you have access
base_model: google/gemma-2b
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
# huggingface repo
datasets:
- path: OdiaGenAIdata/culturax-odia
type: completion
val_set_size: 0.1
output_dir: ./gemma-odia-2b-pretrain
hub_model_id: sam2ai/gemma_odia_2b
adapter: qlora
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
wandb_project: gemma-completion-2b-odia
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 3
micro_batch_size: 2
num_epochs: 10
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: false
warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
gemma_odia_2b
This model is a fine-tuned version of google/gemma-2b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 13.3986
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 87
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 48.3127 | 0.0 | 1 | 48.2905 |
| 21.4891 | 0.25 | 449 | 21.4957 |
| 25.8116 | 0.5 | 898 | 26.0510 |
| 25.3858 | 0.75 | 1347 | 25.6013 |
| 16.9215 | 1.0 | 1796 | 16.9936 |
| 16.7894 | 1.24 | 2245 | 16.7975 |
| 16.8564 | 1.49 | 2694 | 17.0068 |
| 16.8912 | 1.74 | 3143 | 17.0482 |
| 16.9407 | 1.99 | 3592 | 17.0556 |
| 16.7487 | 2.22 | 4041 | 16.8123 |
| 17.7797 | 2.47 | 4490 | 18.1220 |
| 14.0039 | 2.72 | 4939 | 14.0630 |
| 14.7386 | 2.97 | 5388 | 14.7828 |
| 14.9965 | 3.21 | 5837 | 15.2212 |
| 15.1822 | 3.46 | 6286 | 15.6448 |
| 14.1876 | 3.71 | 6735 | 14.5398 |
| 16.6416 | 3.96 | 7184 | 16.9006 |
| 17.0568 | 4.19 | 7633 | 17.1808 |
| 17.4472 | 4.44 | 8082 | 17.5766 |
| 17.4219 | 4.69 | 8531 | 17.5393 |
| 17.3064 | 4.94 | 8980 | 17.5467 |
| 17.2741 | 5.18 | 9429 | 17.5657 |
| 16.9905 | 5.43 | 9878 | 17.3912 |
| 16.642 | 5.68 | 10327 | 17.1920 |
| 16.6345 | 5.93 | 10776 | 17.1085 |
| 15.5702 | 6.16 | 11225 | 16.0494 |
| 15.3421 | 6.41 | 11674 | 15.9889 |
| 13.1025 | 6.66 | 12123 | 13.1419 |
| 13.1904 | 6.91 | 12572 | 13.2151 |
| 13.261 | 7.15 | 13021 | 13.3119 |
| 13.2333 | 7.4 | 13470 | 13.3195 |
| 13.2705 | 7.65 | 13919 | 13.3380 |
| 13.3417 | 7.9 | 14368 | 13.3804 |
| 13.3553 | 8.13 | 14817 | 13.3902 |
| 13.4078 | 8.38 | 15266 | 13.4614 |
| 13.394 | 8.63 | 15715 | 13.4338 |
| 13.3754 | 8.88 | 16164 | 13.4149 |
| 13.3487 | 9.12 | 16613 | 13.4044 |
| 13.3807 | 9.37 | 17062 | 13.3903 |
| 13.3766 | 9.62 | 17511 | 13.3986 |
Framework versions
- PEFT 0.9.0
- Transformers 4.40.0.dev0
- Pytorch 2.4.0.dev20240326+rocm6.0
- Datasets 2.18.0
- Tokenizers 0.15.0