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YoungPanda / continued_pretrian
Model's Last Updated: March 17 2024
text-generation
Introduction of continued_pretrian
Model Details of continued_pretrian
See axolotl config
axolotl version:
0.4.0
base_model: Equall/Saul-Base
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: Drewskidang/chatlaw
type: sharegpt
conversation: chatml
- path: Drewskidang/tool
type: sharegpt
conversation: chatml
- path: digitalpipelines/samantha-1.1-uncensored
type: sharegpt
conversation: chatml
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./out
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false
wandb_project: mistral_chat
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 6
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00005
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
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-4
warmup_steps: 100
evals_per_epoch: 4
eval_table_size:
eval_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>"
tokens: # these are delimiters
- "<|im_start|>"
- "<|im_end|>"
out
This model is a fine-tuned version of Equall/Saul-Base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1824
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: 5e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 96
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=0.0001
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5436 | 0.18 | 1 | 1.5013 |
| 1.5336 | 0.36 | 2 | 1.4939 |
| 1.4731 | 0.73 | 4 | 1.4126 |
| 1.3819 | 1.09 | 6 | 1.3104 |
| 1.312 | 1.27 | 8 | 1.2592 |
| 1.254 | 1.64 | 10 | 1.1824 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0
Runs of YoungPanda continued_pretrian on huggingface.co
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More Information About continued_pretrian huggingface.co Model
Url of continued_pretrian
continued_pretrian huggingface.co Url
Provider of continued_pretrian huggingface.co
Other API from YoungPanda
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