Kibalama/checkpoint

README.md

@@ -1,69 +1,59 @@
 ---
-base_model: unsloth/gemma-3-1b-it-unsloth-bnb-4bit
-library_name: transformers
-model_name: outputs
+library_name: peft
+license: apache-2.0
+base_model: unsloth/whisper-small
 tags:
-- generated_from_trainer
+- base_model:adapter:unsloth/whisper-small
+- lora
+- transformers
 - unsloth
-- grpo
-- trl
-licence: license
+model-index:
+- name: outputs
+  results: []
 ---
 
-# Model Card for outputs
+<!-- 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. -->
 
-This model is a fine-tuned version of [unsloth/gemma-3-1b-it-unsloth-bnb-4bit](https://huggingface.co/unsloth/gemma-3-1b-it-unsloth-bnb-4bit).
-It has been trained using [TRL](https://github.com/huggingface/trl).
+# outputs
 
-## Quick start
+This model is a fine-tuned version of [unsloth/whisper-small](https://huggingface.co/unsloth/whisper-small) on an unknown dataset.
 
-```python
-from transformers import pipeline
+## Model description
 
-question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
-generator = pipeline("text-generation", model="Kibalama/outputs", device="cuda")
-output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
-print(output["generated_text"])
-```
+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: 3407
+- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 5
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
 
 
-This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
 
 ### Framework versions
 
-- TRL: 0.19.1
-- Transformers: 4.53.2
-- Pytorch: 2.7.0
-- Datasets: 3.6.0
-- Tokenizers: 0.21.2
-
-## Citations
-
-Cite GRPO as:
-
-```bibtex
-@article{zhihong2024deepseekmath,
-    title        = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
-    author       = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
-    year         = 2024,
-    eprint       = {arXiv:2402.03300},
-}
-
-```
-
-Cite TRL as:
-    
-```bibtex
-@misc{vonwerra2022trl,
-	title        = {{TRL: Transformer Reinforcement Learning}},
-	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
-	year         = 2020,
-	journal      = {GitHub repository},
-	publisher    = {GitHub},
-	howpublished = {\url{https://github.com/huggingface/trl}}
-}
-```
+- PEFT 0.17.0
+- Transformers 4.51.3
+- Pytorch 2.8.0+cu126
+- Datasets 3.6.0
+- Tokenizers 0.21.4

adapter_config.json

@@ -1,7 +1,10 @@
 {
   "alpha_pattern": {},
-  "auto_mapping": null,
-  "base_model_name_or_path": "unsloth/gemma-3-1b-it-unsloth-bnb-4bit",
+  "auto_mapping": {
+    "base_model_class": "WhisperForConditionalGeneration",
+    "parent_library": "transformers.models.whisper.modeling_whisper"
+  },
+  "base_model_name_or_path": "unsloth/whisper-small",
   "bias": "none",
   "corda_config": null,
   "eva_config": null,
@@ -13,27 +16,23 @@
   "layers_pattern": null,
   "layers_to_transform": null,
   "loftq_config": {},
-  "lora_alpha": 32,
+  "lora_alpha": 64,
   "lora_bias": false,
-  "lora_dropout": 0.0,
+  "lora_dropout": 0,
   "megatron_config": null,
   "megatron_core": "megatron.core",
   "modules_to_save": null,
   "peft_type": "LORA",
   "qalora_group_size": 16,
-  "r": 32,
+  "r": 64,
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "gate_proj",
     "q_proj",
-    "up_proj",
-    "o_proj",
-    "v_proj",
-    "k_proj",
-    "down_proj"
+    "v_proj"
   ],
-  "task_type": "CAUSAL_LM",
+  "target_parameters": null,
+  "task_type": null,
   "trainable_token_indices": null,
   "use_dora": false,
   "use_qalora": false,

adapter_model.safetensors

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+size 28331952

preprocessor_config.json

@@ -0,0 +1,15 @@
+{
+  "chunk_length": 30,
+  "dither": 0.0,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 80,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

training_args.bin

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