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ucalyptus / prem-1B-chat-32k
Model's Last Updated: May 11 2024
Introduction of prem-1B-chat-32k
Model Details of prem-1B-chat-32k
See axolotl config
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|>
prem-1B-chat-32k
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:
- Loss: 6.9843
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 20
Training results
| 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 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
Runs of ucalyptus prem-1B-chat-32k on huggingface.co
1
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs
More Information About prem-1B-chat-32k huggingface.co Model
Url of prem-1B-chat-32k
prem-1B-chat-32k huggingface.co Url
Provider of prem-1B-chat-32k huggingface.co
Other API from ucalyptus
Total runs:
19
Run Growth:
9
Growth Rate:
47.37%
Total runs:
12
Run Growth:
12
Growth Rate:
100.00%
Total runs:
7
Run Growth:
-2
Growth Rate:
-28.57%
Total runs:
5
Run Growth:
-1
Growth Rate:
-20.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%
Total runs:
0
Run Growth:
0
Growth Rate:
0.00%