Prem
Collection
Finetunes and Quantizations of the Prem LLMs
•
11 items
•
Updated
•
2
axolotl version: 0.4.0
base_model: premai-io/prem-1B-chat
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: argilla/distilabel-capybara-dpo-7k-binarized
type: orpo.chat_template
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: ./prem-1B-chat-32k
save_safetensors: true
sequence_len: 8192
sample_packing: false
pad_to_sequence_len: false
use_pose: true
pose_max_context_len: 262144
min_sample_len: 6144
pose_num_chunks: 16
curriculum_sampling: true
overrides_of_model_config:
rope_theta: 500000.0
max_position_embeddings: 262144
# peft_use_dora: true
adapter: lora
peft_use_rslora: true
lora_model_dir:
lora_r: 1024
lora_alpha: 1024
lora_dropout: 0.1
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lora_modules_to_save:
- embed_tokens
- lm_head
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 20
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00001
max_grad_norm: 1.0
adam_beta2: 0.95
train_on_inputs: false
group_by_length: false
bf16: true
fp16:
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
sdp_attention:
s2_attention:
warmup_steps: 10
evals_per_epoch: 8
saves_per_epoch: 8
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
pad_token: <|end_of_text|>
This model is a fine-tuned version of premai-io/prem-1B-chat on the Argilla DPO dataset. 32K context extended using PoSE method It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.5389 | 1.0 | 1 | 6.3469 |
0.5389 | 2.0 | 2 | 6.2533 |
0.5017 | 3.0 | 3 | 6.2101 |
0.4689 | 4.0 | 4 | 6.3163 |
0.3604 | 5.0 | 5 | 6.4144 |
0.3107 | 6.0 | 6 | 6.4127 |
0.2698 | 7.0 | 7 | 6.8089 |
0.317 | 8.0 | 8 | 7.3388 |
0.2228 | 9.0 | 9 | 6.5063 |
0.1798 | 10.0 | 10 | 5.7073 |
0.1436 | 11.0 | 11 | 5.1185 |
0.1183 | 12.0 | 12 | 4.8994 |
0.1002 | 13.0 | 13 | 4.8033 |
0.0865 | 14.0 | 14 | 5.1707 |
0.0758 | 15.0 | 15 | 5.7089 |
0.0663 | 16.0 | 16 | 6.4052 |
0.0601 | 17.0 | 17 | 6.7814 |
0.0545 | 18.0 | 18 | 6.9586 |
0.0505 | 19.0 | 19 | 6.9766 |
0.0482 | 20.0 | 20 | 6.9843 |
Base model
premai-io/prem-1B-chat