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🚨🚨🚨Deprecate evaluation_strategy to eval_strategy🚨🚨🚨 (#30190)

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This commit is contained in:
Zach Mueller
2024-04-18 12:49:43 -04:00
committed by GitHub
parent c86d020ead
commit 60d5f8f9f0
116 changed files with 214 additions and 203 deletions
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2
examples/pytorch/README.md
View File

@@ -283,7 +283,7 @@ To enable Neptune logging, in your `TrainingArguments`, set the `report_to` argu
```python
training_args = TrainingArguments(
"quick-training-distilbert-mrpc",
evaluation_strategy="steps",
eval_strategy="steps",
eval_steps=20,
report_to="neptune",
)

4
examples/pytorch/audio-classification/README.md
View File

@@ -50,7 +50,7 @@ python run_audio_classification.py \
--dataloader_num_workers 4 \
--logging_strategy steps \
--logging_steps 10 \
--evaluation_strategy epoch \
--eval_strategy epoch \
--save_strategy epoch \
--load_best_model_at_end True \
--metric_for_best_model accuracy \
@@ -92,7 +92,7 @@ python run_audio_classification.py \
--dataloader_num_workers 8 \
--logging_strategy steps \
--logging_steps 10 \
--evaluation_strategy epoch \
--eval_strategy epoch \
--save_strategy epoch \
--load_best_model_at_end True \
--metric_for_best_model accuracy \

2
examples/pytorch/image-classification/README.md
View File

@@ -52,7 +52,7 @@ python run_image_classification.py \
--per_device_eval_batch_size 8 \
--logging_strategy steps \
--logging_steps 10 \
--evaluation_strategy epoch \
--eval_strategy epoch \
--save_strategy epoch \
--load_best_model_at_end True \
--save_total_limit 3 \

6
examples/pytorch/image-pretraining/README.md
View File

@@ -56,7 +56,7 @@ Alternatively, one can decide to further pre-train an already pre-trained (or fi
--per_device_eval_batch_size 8 \
--logging_strategy steps \
--logging_steps 10 \
--evaluation_strategy epoch \
--eval_strategy epoch \
--save_strategy epoch \
--load_best_model_at_end True \
--save_total_limit 3 \
@@ -106,7 +106,7 @@ Next, we can run the script by providing the path to this custom configuration (
--per_device_eval_batch_size 8 \
--logging_strategy steps \
--logging_steps 10 \
--evaluation_strategy epoch \
--eval_strategy epoch \
--save_strategy epoch \
--load_best_model_at_end True \
--save_total_limit 3 \
@@ -172,7 +172,7 @@ python run_mae.py \
--per_device_eval_batch_size 8 \
--logging_strategy steps \
--logging_steps 10 \
--evaluation_strategy epoch \
--eval_strategy epoch \
--save_strategy epoch \
--load_best_model_at_end True \
--save_total_limit 3 \

2
examples/pytorch/semantic-segmentation/README.md
View File

@@ -118,7 +118,7 @@ python run_semantic_segmentation.py \
--per_device_eval_batch_size 8 \
--logging_strategy steps \
--logging_steps 100 \
--evaluation_strategy epoch \
--eval_strategy epoch \
--save_strategy epoch \
--seed 1337
```

18
examples/pytorch/speech-recognition/README.md
View File

@@ -76,7 +76,7 @@ python run_speech_recognition_ctc.py \
--gradient_accumulation_steps="2" \
--learning_rate="3e-4" \
--warmup_steps="500" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--text_column_name="sentence" \
--length_column_name="input_length" \
--save_steps="400" \
@@ -111,7 +111,7 @@ torchrun \
--per_device_train_batch_size="4" \
--learning_rate="3e-4" \
--warmup_steps="500" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--text_column_name="sentence" \
--length_column_name="input_length" \
--save_steps="400" \
@@ -162,7 +162,7 @@ However, the `--shuffle_buffer_size` argument controls how many examples we can
--gradient_accumulation_steps="2" \
--learning_rate="5e-4" \
--warmup_steps="500" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--text_column_name="sentence" \
--save_steps="500" \
--eval_steps="500" \
@@ -293,7 +293,7 @@ python run_speech_recognition_ctc.py \
--per_device_train_batch_size="32" \
--learning_rate="1e-3" \
--warmup_steps="100" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--text_column_name="sentence" \
--length_column_name="input_length" \
--save_steps="200" \
@@ -330,7 +330,7 @@ python run_speech_recognition_ctc.py \
--per_device_train_batch_size="32" \
--learning_rate="1e-3" \
--warmup_steps="100" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--text_column_name="sentence" \
--length_column_name="input_length" \
--save_steps="200" \
@@ -378,7 +378,7 @@ python run_speech_recognition_seq2seq.py \
--logging_steps="25" \
--learning_rate="1e-5" \
--warmup_steps="500" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--eval_steps="1000" \
--save_strategy="steps" \
--save_steps="1000" \
@@ -419,7 +419,7 @@ torchrun \
--logging_steps="25" \
--learning_rate="1e-5" \
--warmup_steps="500" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--eval_steps="1000" \
--save_strategy="steps" \
--save_steps="1000" \
@@ -547,7 +547,7 @@ python run_speech_recognition_seq2seq.py \
--gradient_accumulation_steps="8" \
--learning_rate="3e-4" \
--warmup_steps="400" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--text_column_name="text" \
--save_steps="400" \
--eval_steps="400" \
@@ -589,7 +589,7 @@ torchrun \
--gradient_accumulation_steps="1" \
--learning_rate="3e-4" \
--warmup_steps="400" \
--evaluation_strategy="steps" \
--eval_strategy="steps" \
--text_column_name="text" \
--save_steps="400" \
--eval_steps="400" \