---
library_name: transformers
license: apache-2.0
base_model: Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors
tags:
- axolotl
- generated_from_trainer
datasets:
- Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled
model-index:
- name: magnifi-module-classifier-04-17-relabelled-upsampled
  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: `0.16.0.dev0`
```yaml
base_model: Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors
hub_model_id: Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled

load_in_8bit: false
load_in_4bit: false
strict: false

chat_template: qwen3
datasets:
  - path: Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled
    type: chat_template
    split: train
    field_messages: messages
    message_property_mappings:
      role: role
      content: content

val_set_size: 0.1

output_dir: /workspace/data/outputs/qwen3-4B/fft_magnifi-module-classifier-04-17-relabelled-upsampled/
dataset_prepared_path: /workspace/data/datasets_prepared/magnifi-module-classifier-04-17-relabelled-upsampled

sequence_len: 16000
sample_packing: true
eval_sample_packing: true


wandb_project: sage-classifier
wandb_entity:
wandb_watch:
wandb_name: magnifi-module-classifier-04-17-relabelled-upsampled
wandb_log_model: 

gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_torch_fused
lr_scheduler: cosine
learning_rate: 2e-5

bf16: auto
tf32: true

resume_from_checkpoint:
logging_steps: 1

evals_per_epoch: 2
saves_per_epoch: 1

warmup_ratio: 0.1
weight_decay: 0.0
fsdp:
  - full_shard
  - auto_wrap

fsdp_config:
  fsdp_version: 2
  fsdp_offload_params: false
  fsdp_cpu_ram_efficient_loading: true
  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
  fsdp_transformer_layer_cls_to_wrap: Qwen3DecoderLayer
  fsdp_state_dict_type: FULL_STATE_DICT
  fsdp_sharding_strategy: FULL_SHARD
  fsdp_reshard_after_forward: true
  fsdp_activation_checkpointing: true

special_tokens:

```

</details><br>

# magnifi-module-classifier-04-17-relabelled-upsampled

This model is a fine-tuned version of [Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors](https://huggingface.co/Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors) on the Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2227
- Ppl: 1.2494
- Memory/max Active (gib): 34.91
- Memory/max Allocated (gib): 34.91
- Memory/device Reserved (gib): 57.25

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 47
- training_steps: 478

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Ppl    | Active (gib) | Allocated (gib) | Reserved (gib) |
|:-------------:|:------:|:----:|:---------------:|:------:|:------------:|:---------------:|:--------------:|
| No log        | 0      | 0    | 0.2049          | 1.2275 | 27.41        | 27.41           | 30.62          |
| 0.2339        | 0.5    | 120  | 0.2288          | 1.2571 | 34.91        | 34.91           | 59.04          |
| 0.2290        | 1.0    | 240  | 0.2166          | 1.2419 | 34.91        | 34.91           | 57.54          |
| 0.0898        | 1.5    | 360  | 0.2251          | 1.2524 | 34.91        | 34.91           | 57.54          |
| 0.1331        | 1.9917 | 478  | 0.2227          | 1.2494 | 34.91        | 34.91           | 57.25          |


### Framework versions

- Transformers 5.5.4
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2