update audio classification script

audio_classification_scripts/run_mms_lid.sh

 #!/usr/bin/env bash
 
-python run_audio_classification.py \
-    --model_name_or_path "facebook/mms-lid-126" \
+CUDA_VISIBLE_DEVICES=2 python run_audio_classification_one_layer.py \
+    --model_name_or_path "facebook/mms-lid-4017" \
     --train_dataset_name "stable-speech/concatenated-normalized-accent-dataset" \
     --train_dataset_config_name "default" \
     --train_split_name "train" \
@@ -10,11 +10,11 @@ python run_audio_classification.py \
     --eval_dataset_config_name "default" \
     --eval_split_name "test" \
     --eval_label_column_name "labels" \
-    --output_dir "./" \
+    --output_dir "./tmp/" \
     --do_train \
     --do_eval \
     --overwrite_output_dir \
-    --remove_unused_columns False \
+    --remove_unused_columns false \
     --fp16 \
     --fp16_full_eval \
     --learning_rate 1e-4 \
@@ -30,9 +30,11 @@ python run_audio_classification.py \
     --logging_strategy "steps" \
     --logging_steps 10 \
     --evaluation_strategy "steps" \
-    --eval_steps 500 \
+    --eval_steps 300 \
     --save_strategy "no" \
     --save_steps 2000 \
-    --freeze_base_model True \
-    --push_to_hub False \
-    --trust_remote_code
+    --freeze_base_model true \
+    --freeze_feature_encoder true \
+    --push_to_hub false \
+    --trust_remote_code \
+    --use_weighted_layer_sum true \

audio_classification_scripts/run_sweep.yaml

 command:
   - python3
   - ${program}
-  - --load_best_model_at_end
   - --fp16
   - --fp16_full_eval
   - --do_train
   - --do_eval
   - --trust_remote_code
   - --overwrite_output_dir
-  - --ignore_mismatched_sizes
-  - --gradient_checkpointing
   - ${args}
-method: grid
+method: random
 metric:
   goal: maximize
   name: eval/accuracy
 parameters:
   model_name_or_path:
-    value: facebook/mms-lid-126
+    value: facebook/mms-lid-4017
   train_dataset_name:
-    value: stable-speech/concatenated-accent-dataset
+    value:  "stable-speech/concatenated-normalized-accent-dataset+stable-speech/concatenated-common-voice-15-accented"
   train_dataset_config_name:
-    value: default
+    value: "default+default"
   train_split_name:
-    value: train
+    value: "train+train"
   train_label_column_name:
-    value: labels
+    value: "labels+labels"
   eval_dataset_name:
-    value: stable-speech/concatenated-accent-dataset
+    value: stable-speech/concatenated-normalized-accent-dataset
   eval_dataset_config_name:
     value: default
   eval_split_name:
@@ -35,31 +32,38 @@ parameters:
   eval_label_column_name:
     value: labels
   output_dir:
-    value: ./
+    value: "/raid/yoach/tmp/"
   remove_unused_columns:
     value: false
   learning_rate:
-    value: 1e-4
+    distribution: log_uniform_values
+    min: 3e-6
+    max: 0.01
   lr_scheduler_type:
-    value: constant_with_warmup
+    value: constant
   max_length_seconds:
     value: 20  # give some data diversity for longer audio samples
   min_length_seconds:
-    value: 7
+    value: 5
   attention_mask:
-    value: true
-  warmup_steps:
-    value: 100
-  max_steps:
-    value: 2000
+    values:
+    - true
+  num_train_epochs:
+    values:
+      - 2
+      - 5
+      - 10
+      - 20
+      - 40
+      - 60
   per_device_train_batch_size:
     value: 32
   per_device_eval_batch_size:
-    value: 16
+    value: 32
   preprocessing_num_workers:
-    value: 4
+    value: 8
   dataloader_num_workers:
-    value: 4
+    value: 8
   logging_strategy:
     value: steps
   logging_steps:
@@ -67,20 +71,28 @@ parameters:
   evaluation_strategy:
     value: steps
   eval_steps:
-    value: 1000
+    value: 2000
   save_strategy:
-    value: steps
+    value: "no"
   save_steps:
     value: 2000
   metric_for_best_model:
     value: accuracy
-  freeze_base_model:
-    values:
-     - false
-     - true
-  group_by_length:
-    value: false  # TODO(SG): batch by length
   push_to_hub:
     value: false
+  use_weighted_layer_sum:
+    value: false
+  freeze_base_model:
+    value: true
+  max_samples_per_label:
+    value: 10000
+  save_to_disk:
+    value: "/raid/yoach/tmp_dataset_accents/" 
+  temporary_save_to_disk:
+    value: "/raid/yoach/tmp_hidden_states/"
+  use_last_embedding_layer:
+    value: true
+  filter_threshold:
+    value: "0.001"
 program: run_audio_classification.py
-project: mms-lid-accent-classification
+project: mms-lid-accent-classification-v2
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