---
library_name: transformers
license: cc-by-nc-4.0
base_model: hardlyworking/4Bcpt
tags:
- axolotl
- generated_from_trainer
datasets:
- GreenerPastures/All-Your-Base-Full
model-index:
- name: 4Brp
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.11.0.dev0`
```yaml
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>

# 4Brp

This model is a fine-tuned version of [hardlyworking/4Bcpt](https://huggingface.co/hardlyworking/4Bcpt) on the GreenerPastures/All-Your-Base-Full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9183

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 57
- training_steps: 1148

### Training results

| 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          |


### Framework versions

- Transformers 4.53.1
- Pytorch 2.6.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2