Update README.md

README.md

@@ -9,11 +9,36 @@ tags:
 - music
 - instrument
 pipeline_tag: audio-to-audio
+model-index:
+- name: Mistral_MidiTok_Transformer_Single_Instrument_Small
+  results: []
 ---
 
+# Mistral_MidiTok_Transformer_Single_Instrument_Small
 
 This model is trained from scratch using tokenized midi music.
 I have trained a MidiTok tokeniser (REMI) and its made by spliting multi-track midi into a single track. 
 
 We then trained in on a small dataset.
-Its using the Mistral model that has been cut down quite a bit.
+Its using the Mistral model that has been cut down quite a bit.
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 30
+- eval_batch_size: 30
+- seed: 444
+- gradient_accumulation_steps: 3
+- total_train_batch_size: 90
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_ratio: 0.3
+- training_steps: 20000
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.1.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3