| --- |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: intervitens/internlm2-base-20b-llama |
| model-index: |
| - name: internlm-limarp-lora |
| results: [] |
| --- |
| |
| Don't use this yet, there's a problem with the llamafied internlm2 tokenizer. |
| Prompt format: ChatML. |
|
|
| [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
| <details><summary>See axolotl config</summary> |
|
|
| axolotl version: `0.3.0` |
| ```yaml |
| base_model: /data/internlm2-base-20b-llama |
| model_type: LlamaForCausalLM |
| tokenizer_type: LlamaTokenizer |
| is_llama_derived_model: true |
| |
| load_in_8bit: true |
| load_in_4bit: false |
| strict: false |
| |
| datasets: |
| - path: /data/train-all-8k.jsonl |
| type: completion |
| dataset_prepared_path: |
| val_set_size: 0.05 |
| output_dir: /data/internlm-limarp-lora-out |
| |
| sequence_len: 8192 |
| sample_packing: true |
| pad_to_sequence_len: true |
| |
| adapter: lora |
| lora_model_dir: |
| lora_r: 128 |
| lora_alpha: 64 |
| lora_dropout: 0.05 |
| lora_target_linear: true |
| lora_fan_in_fan_out: |
| |
| gradient_accumulation_steps: 4 |
| micro_batch_size: 2 |
| num_epochs: 4 |
| optimizer: adamw_bnb_8bit |
| lr_scheduler: cosine |
| learning_rate: 0.00002 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: true |
| fp16: false |
| tf32: false |
| |
| gradient_checkpointing: true |
| gradient_checkpointing_kwargs: |
| early_stopping_patience: |
| resume_from_checkpoint: |
| local_rank: |
| logging_steps: 1 |
| xformers_attention: |
| flash_attention: true |
| s2_attention: |
| |
| warmup_steps: 10 |
| evals_per_epoch: 4 |
| eval_table_size: |
| eval_table_max_new_tokens: 128 |
| saves_per_epoch: 1 |
| debug: |
| deepspeed: |
| weight_decay: 0.0 |
| fsdp: |
| fsdp_config: |
| special_tokens: |
| bos_token: "<s>" |
| eos_token: "</s>" |
| unk_token: "<unk>" |
| |
| ``` |
|
|
| </details><br> |
|
|
| # internlm-limarp-lora |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.1216 |
|
|
| ## 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: True |
| - load_in_4bit: False |
| - 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: fp4 |
| - bnb_4bit_use_double_quant: False |
| - bnb_4bit_compute_dtype: float32 |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 2.3563 | 0.01 | 1 | 2.3995 | |
| | 2.1815 | 0.25 | 37 | 2.2693 | |
| | 2.1364 | 0.51 | 74 | 2.1684 | |
| | 2.1355 | 0.76 | 111 | 2.1526 | |
| | 2.1624 | 1.03 | 148 | 2.1435 | |
| | 2.1326 | 1.28 | 185 | 2.1367 | |
| | 1.9987 | 1.54 | 222 | 2.1330 | |
| | 2.0494 | 1.79 | 259 | 2.1291 | |
| | 2.0505 | 2.04 | 296 | 2.1266 | |
| | 2.075 | 2.3 | 333 | 2.1243 | |
| | 2.0183 | 2.55 | 370 | 2.1229 | |
| | 2.1047 | 2.81 | 407 | 2.1227 | |
| | 2.1309 | 3.06 | 444 | 2.1218 | |
| | 2.1249 | 3.31 | 481 | 2.1214 | |
| | 2.1423 | 3.57 | 518 | 2.1214 | |
| | 2.0913 | 3.82 | 555 | 2.1216 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.7.0 |
| - Transformers 4.37.0.dev0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
| |
