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amphora / plain-lm3-100k-lora
Model's Last Updated: July 23 2024
Introduction of plain-lm3-100k-lora
Model Details of plain-lm3-100k-lora
See axolotl config
axolotl version:
0.4.1
base_model: NousResearch/Meta-Llama-3-8B-Instruct
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: true
load_in_4bit: false
strict: false
chat_template: llama3
datasets:
- path: k2-eval-full.jsonl
type: chat_template
chat_template: llama3
field_messages: message
message_field_role: role
message_field_content: content
roles:
user:
- user
assistant:
- assistant
val_set_size: 0.01
output_dir: ./outputs/lora-out
sequence_len: 4096
sample_packing: false
pad_to_sequence_len: false
adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project: fincode
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 32
micro_batch_size: 8
num_epochs: 3
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: true
s2_attention:
deepspeed: deepspeed_configs/zero1.json
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 2
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
pad_token: <|end_of_text|>
outputs/lora-out
This model is a fine-tuned version of NousResearch/Meta-Llama-3-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9072
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4939 | 0.0108 | 1 | 1.2541 |
| 1.2413 | 0.2485 | 23 | 1.0233 |
| 1.1686 | 0.4970 | 46 | 0.9725 |
| 1.1344 | 0.7454 | 69 | 0.9506 |
| 1.0826 | 0.9939 | 92 | 0.9353 |
| 1.1045 | 1.2424 | 115 | 0.9285 |
| 1.0803 | 1.4909 | 138 | 0.9215 |
| 1.0649 | 1.7394 | 161 | 0.9138 |
| 1.0492 | 1.9878 | 184 | 0.9110 |
| 1.061 | 2.2363 | 207 | 0.9092 |
| 1.0397 | 2.4848 | 230 | 0.9081 |
| 1.0357 | 2.7333 | 253 | 0.9068 |
| 1.025 | 2.9818 | 276 | 0.9072 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
Runs of amphora plain-lm3-100k-lora on huggingface.co
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More Information About plain-lm3-100k-lora huggingface.co Model
Url of plain-lm3-100k-lora
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Provider of plain-lm3-100k-lora huggingface.co
Other API from amphora
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