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hardlyworking/4Brp
4Brp is a text generation model from hardlyworking. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
axolotl version: 0.11.0.dev0
base_model: hardlyworking/4Bcpt
load_in_8bit: false
load_in_4bit: false
strict: false
chat_template: chatml
datasets:
- path: GreenerPastures/All-Your-Base-Full
type: chat_template
split: train
field_messages: conversations
message_property_mappings:
role: from
content: value
val_set_size: 0.02
output_dir: ./outputs/out
dataset_prepared_path: last_run_prepared
shuffle_merged_datasets: true
hub_model_id: hardlyworking/4Brp
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true
plugins:
- axolotl.integrations.liger.LigerPlugin
- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: false
cut_cross_entropy: true
sequence_len: 32768
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true
wandb_project: New4B
wandb_entity:
wandb_watch:
wandb_name: New4Brp
wandb_log_model:
evals_per_epoch: 8
eval_table_size:
eval_max_new_tokens: 128
gradient_accumulation_steps: 2
micro_batch_size: 8
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 1e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: offload
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:
deepspeed:
warmup_ratio: 0.05
saves_per_epoch: 1
debug:
weight_decay: 0.01
fsdp:
fsdp_config:
special_tokens:
pad_token: <|endoftext|>
</details><br>
This model is a fine-tuned version of hardlyworking/4Bcpt on the GreenerPastures/All-Your-Base-Full dataset. 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 |
|---|---|---|---|
| No log | 0 | 0 | 1.1370 |
| 1.0053 | 0.1253 | 72 | 0.9893 |
| 0.9679 | 0.2507 | 144 | 0.9576 |
| 0.966 | 0.3760 | 216 | 0.9440 |
| 0.9397 | 0.5013 | 288 | 0.9358 |
| 0.9563 | 0.6266 | 360 | 0.9300 |
| 0.9034 | 0.7520 | 432 | 0.9259 |
| 0.9214 | 0.8773 | 504 | 0.9230 |
| 0.9155 | 1.0017 | 576 | 0.9211 |
| 0.9072 | 1.1271 | 648 | 0.9198 |
| 0.893 | 1.2524 | 720 | 0.9191 |
| 0.91 | 1.3777 | 792 | 0.9186 |
| 0.9649 | 1.5030 | 864 | 0.9184 |
| 0.8838 | 1.6284 | 936 | 0.9183 |
| 0.8856 | 1.7537 | 1008 | 0.9183 |
| 0.9235 | 1.8790 | 1080 | 0.9183 |