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Lambent / CosMoE-Lisa-4x1b
Model's Last Updated: June 30 2025
text-generation
Introduction of CosMoE-Lisa-4x1b
Model Details of CosMoE-Lisa-4x1b
| Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
|---|---|---|---|---|---|
| CosMoE-Lisa-4x1b | 23.42 | 43.56 | 38.11 | 28.35 | 33.36 |
Ambitious training, but appears to have decreased capabilities rather than aided them. Lessons learned.
See axolotl config
axolotl version:
0.4.0
base_model: Lambent/cosmoem-4x1b
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: Vezora/Tested-22k-Python-Alpaca
type: alpaca
- path: teknium/GPTeacher-General-Instruct #89.3k
type: gpteacher
- path: HuggingFaceTB/cosmopedia-100k
type: completion
dataset_prepared_path: prepared-education
val_set_size: 0.05
output_dir: ./lisa-out
sequence_len: 2048
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
lisa_n_layers: 4
lisa_step_interval: 10
lisa_layers_attribute: model.layers
adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:
wandb_project: CosMoE-Lisa-4x1b
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0005
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: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 20
evals_per_epoch: 2
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.002
fsdp:
fsdp_config:
special_tokens:
lisa-out
This model is a fine-tuned version of Lambent/cosmoem-4x1b on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8891 | 0.0 | 1 | nan |
| 2.1984 | 0.5 | 30501 | nan |
| 1.5296 | 1.0 | 61002 | nan |
| 1.4647 | 1.49 | 91503 | nan |
| 1.4698 | 1.99 | 122004 | nan |
Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.0
Runs of Lambent CosMoE-Lisa-4x1b on huggingface.co
11
Total runs
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24-hour runs
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3-day runs
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7-day runs
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30-day runs
More Information About CosMoE-Lisa-4x1b huggingface.co Model
Url of CosMoE-Lisa-4x1b
CosMoE-Lisa-4x1b huggingface.co Url
Provider of CosMoE-Lisa-4x1b huggingface.co
Other API from Lambent
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