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Complete Spark-TTS with Arabic fine-tuned LLM
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metadata
library_name: transformers
tags:
  - generated_from_trainer
datasets:
  - /content/processed_output/clartts_data.jsonl
model-index:
  - name: content/finetuned_model
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.13.0.dev0

base_model: /content/SparkTTS-Finetune/pretrained_models/Spark-TTS-0.5B/LLM
load_in_4bit: false
load_in_8bit: false

trust_remote_code: true
strict: false

datasets:
  - path: /content/processed_output/clartts_data.jsonl
    type: completion

dataset_prepared_path:
val_set_size: 0.05
output_dir: /content/finetuned_model

sequence_len: 1024
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: true

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_torch_fused
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false

early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 50
xformers_attention:
flash_attention: false

warmup_steps: 10
evals_per_epoch: 1
save_steps: 200
debug:
deepspeed:
weight_decay: 0.0

content/finetuned_model

This model was trained from scratch on the /content/processed_output/clartts_data.jsonl dataset. It achieves the following results on the evaluation set:

  • Loss: 4.4637
  • Memory/max Active (gib): 7.2
  • Memory/max Allocated (gib): 7.2
  • Memory/device Reserved (gib): 7.62

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 8
  • 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: 10
  • training_steps: 1016

Training results

Training Loss Epoch Step Validation Loss Active (gib) Allocated (gib) Reserved (gib)
No log 0 0 11.8503 3.1 3.1 3.2
4.7248 1.0 339 4.6423 7.2 7.2 7.67
4.3688 2.0 678 4.4637 7.2 7.2 7.62

Framework versions

  • Transformers 4.57.1
  • Pytorch 2.7.1+cu118
  • Datasets 4.4.1
  • Tokenizers 0.22.1