---
library_name: peft
base_model: sudoping01/bambara-llm-exp3-merged
tags:
- axolotl
- base_model:adapter:sudoping01/bambara-llm-exp3-merged
- lora
- transformers
datasets:
- instruction_dataset_asr_axolotl_format.jsonl
pipeline_tag: text-generation
model-index:
- name: bambara-asr-llm-exp1
  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: `0.12.2`
```yaml
base_model: sudoping01/bambara-llm-exp3-merged
processor_type: AutoProcessor
hub_model_id: sudoping01/bambara-asr-llm-exp1

plugins:
  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
cut_cross_entropy: true


skip_prepare_dataset: true  
remove_unused_columns: false
sample_packing: false


ddp: true
ddp_find_unused_parameters: true

# Template and tokens
chat_template: gemma3n
eot_tokens:
  - <end_of_turn>
special_tokens:
  eot_token: <end_of_turn>


datasets:
  - path: instruction_dataset_asr_axolotl_format.jsonl
    type: chat_template


val_set_size: 0.01
output_dir: ./outputs/bambara-gemma3n-asr-lora-exp1-v2


adapter: lora
lora_r: 64  # Reduced from 64 for stability
lora_alpha: 128  # Reduced from 128 for stability
lora_dropout: 0.05
lora_target_modules: 'model.language_model.layers.[\d]+.(mlp|self_attn).(up|down|gate|q|k|v|o)_proj'

# Sequence and batch settings - conservative for audio
sequence_len: 4096  # Reduced from 4096
pad_to_sequence_len: false
micro_batch_size: 8  # Increased: You have 8x H100s, can handle larger batches
gradient_accumulation_steps: 2

# Training parameters
num_epochs: 6  # Start with 1 epoch for testing
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-4  # Slightly higher as per research
warmup_ratio: 0.1  # Increased warmup for multimodal
weight_decay: 0.0  # Set to 0 for multimodal


bf16: true  # Must be true, not auto
tf32: false
load_in_4bit: false  # Keep false for quality
gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false

# Monitoring
logging_steps: 1  # More frequent for debugging
saves_per_epoch: 2
evals_per_epoch: 2

# ASR metrics
metrics:
  - name: wer
  - name: cer
```

</details><br>

# bambara-asr-llm-exp1

This model is a fine-tuned version of [sudoping01/bambara-llm-exp3-merged](https://huggingface.co/sudoping01/bambara-llm-exp3-merged) on the instruction_dataset_asr_axolotl_format.jsonl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0544
- Memory/max Mem Active(gib): 18.76
- Memory/max Mem Allocated(gib): 18.76
- Memory/device Mem Reserved(gib): 19.99

## 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: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Use adamw_8bit 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: 350
- training_steps: 3508

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Mem Active(gib) | Mem Allocated(gib) | Mem Reserved(gib) |
|:-------------:|:------:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|
| No log        | 0      | 0    | 2.3381          | 18.76           | 18.76              | 19.99             |
| 0.4621        | 0.5009 | 293  | 0.5051          | 18.76           | 18.76              | 19.99             |
| 0.3689        | 1.0017 | 586  | 0.3825          | 18.76           | 18.76              | 19.99             |
| 0.3447        | 1.5026 | 879  | 0.3151          | 18.76           | 18.76              | 19.99             |
| 0.2844        | 2.0034 | 1172 | 0.2623          | 18.76           | 18.76              | 19.99             |
| 0.217         | 2.5043 | 1465 | 0.2172          | 18.76           | 18.76              | 19.99             |
| 0.1302        | 3.0051 | 1758 | 0.1837          | 18.76           | 18.76              | 19.99             |
| 0.1559        | 3.5060 | 2051 | 0.1448          | 18.76           | 18.76              | 19.99             |
| 0.1213        | 4.0068 | 2344 | 0.1147          | 18.76           | 18.76              | 19.99             |
| 0.0744        | 4.5077 | 2637 | 0.0851          | 18.76           | 18.76              | 19.99             |
| 0.0555        | 5.0085 | 2930 | 0.0646          | 18.76           | 18.76              | 19.99             |
| 0.0378        | 5.5094 | 3223 | 0.0544          | 18.76           | 18.76              | 19.99             |


### Framework versions

- PEFT 0.17.0
- Transformers 4.55.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4