Update README.md

README.md

@@ -1,12 +1,38 @@
-will edit later:
-
-oading best model from ./checkpoint-1000 (score: 10.968809748023856).
-TrainOutput(global_step=1000, training_loss=0.25546978759765626, metrics={'train_runtime': 62087.7615, 'train_samples_per_second': 1.031, 'train_steps_per_second': 0.016, 'total_flos': 6.531871408128e+19, 'train_loss': 0.25546978759765626, 'epoch': 1.0})
-
-dataset_tags": "mozilla-foundation/common_voice_11_0",
-    "dataset": "Common Voice 11.0", 
-    "language": "es",
-    "model_name": "Whisper Md Ca - 1k",
-    "finetuned_from": "openai/whisper-medium",
-    "tasks": "automatic-speech-recognition",
-    "tags": "whisper-event",
+Whisper Md Ca - 1k
+This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
+
+Loss: 0.2554
+Wer: 10.9688
+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: 1e-05
+train_batch_size: 32
+eval_batch_size: 8
+seed: 42
+gradient_accumulation_steps: 2
+total_train_batch_size: 64
+optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+lr_scheduler_type: linear
+lr_scheduler_warmup_steps: 100
+training_steps: 1000
+mixed_precision_training: Native AMP
+
+Training results
+Training Loss	Epoch	Step	Validation Loss	Wer
+0.2554	1.0	1000	0.2554	10.9688
+Framework versions
+Transformers 4.26.0.dev0
+Pytorch 1.13.1+cu117
+Datasets 2.7.1.dev0
+Tokenizers 0.13.2