updated scripts training norbench

norbench_document_sentiment_bs128.gin

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+from __gin__ import dynamic_registration
+import tasks
+import seqio
+import optax
+
+import __main__ as train_script
+from t5.data import mixtures
+from t5x import models
+from t5x import partitioning
+from t5x import utils
+
+include 't5x/examples/t5/mt5/base.gin'
+include "t5x/configs/runs/finetune.gin"
+
+MIXTURE_OR_TASK_NAME = %gin.REQUIRED
+TASK_FEATURE_LENGTHS = {"inputs": 256, "targets": 256}
+INITIAL_CHECKPOINT_PATH = %gin.REQUIRED
+LR = %gin.REQUIRED
+TRAIN_STEPS = %gin.REQUIRED  # 1000000 pre-trained steps + 10000 fine-tuning steps.
+USE_CACHED_TASKS = False
+DROPOUT_RATE = 0.1
+RANDOM_SEED = 0
+BATCH_SIZE = 128
+EVAL_PERIOD = 1000
+
+#Fixing a small error
+infer_eval/utils.DatasetConfig:
+  task_feature_lengths = %TASK_FEATURE_LENGTHS
+
+#Saving every 500 steps
+utils.SaveCheckpointConfig:
+  period = 1000
+  keep = 1  # number of checkpoints to keep
+
+
+#optax.adamw.weight_decay = 0.1
+#OPTIMIZER = @optax.adamw
+#import t5x.optimizers
+#OPTIMIZER = @optax.adamw
+#optax.adamw.learning_rate = %LR
+#optax.adamw.weight_decay = 0.1
+
+
+utils.create_learning_rate_scheduler:
+  factors = 'constant'
+  base_learning_rate = %LR
+  warmup_steps = 1000
+
+# Might have to ba changed based on architecture
+# partitioning.PjitPartitioner.num_partitions = 1
+
+

norbench_document_sentiment_bs128.sh

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+#!/bin/bash
+PROJECT_DIR=${HOME}"/models/t5-nynorsk-norbench"
+export PYTHONPATH=${PROJECT_DIR}
+echo "PROJECT_DIR is set to: ${PROJECT_DIR}"
+
+
+FINETUNE_STEPS=20000
+EVAL_PREFIX="norbench/norbench_document_sentiment_bs128"
+MODEL_BUCKET_DIR="gs://pere-north-t5x/finetuned/"
+
+CHECKPOINT_LIST=(
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+)
+
+NAME_LIST=(
+  "north_t5_base_NCC_LR_0_0006"
+  "north_t5_base_NCC_LR_0_0008"
+  "north_t5_base_NCC_LR_0_001"
+  "north_t5_base_NCC_LR_0_002"
+)
+
+TASK_LIST=("document_sentiment" "document_sentiment" "document_sentiment" "document_sentiment")
+LR_LIST=(0.0006 0.0008 0.001 0.002)
+
+
+GIN_LIST=(
+  "norbench_document_sentiment_bs128.gin"
+  "norbench_document_sentiment_bs128.gin"
+  "norbench_document_sentiment_bs128.gin"
+  "norbench_document_sentiment_bs128.gin"
+)
+
+START_LIST=(1500000 1500000 1500000 1500000)
+EXP_LIST=(1 2 3 4)
+
+
+op through each experiment in EXP_LIST
+for i in "${!EXP_LIST[@]}"; do
+    INITIAL_CHECKPOINT_PATH="gs://${CHECKPOINT_LIST[i]}"
+    TRAIN_STEPS=$((START_LIST[i]+FINETUNE_STEPS))
+    GIN_FILE=${GIN_LIST[i]}
+    MIXTURE_OR_TASK_NAME=${TASK_LIST[i]}
+    LR=${LR_LIST[i]}
+    EXP=${EXP_LIST[i]}
+    MODEL_DIR="${MODEL_BUCKET_DIR}${EVAL_PREFIX}_exp${EXP}_${NAME_LIST[i]}"
+
+    command="python3 ../../t5x/t5x/train.py --gin_search_paths=\"./\" --gin.TRAIN_STEPS=${TRAIN_STEPS} --gin.LR=${LR}  --gin_file=${GIN_FILE} --gin.INITIAL_CHECKPOINT_PATH=\\\"${INITIAL_CHECKPOINT_PATH}\\\" --gin.MIXTURE_OR_TASK_NAME=\\\"${MIXTURE_OR_TASK_NAME}\\\" --gin.MODEL_DIR=\\\"${MODEL_DIR}\\\""
+    echo "${command}"
+    # Uncomment the next line to run the command:
+    eval "${command}"
+done

norbench_norcola_bs128.gin

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+from __gin__ import dynamic_registration
+import tasks
+import seqio
+import optax
+
+import __main__ as train_script
+from t5.data import mixtures
+from t5x import models
+from t5x import partitioning
+from t5x import utils
+
+include 't5x/examples/t5/mt5/base.gin'
+include "t5x/configs/runs/finetune.gin"
+
+MIXTURE_OR_TASK_NAME = %gin.REQUIRED
+TASK_FEATURE_LENGTHS = {"inputs": 256, "targets": 256}
+INITIAL_CHECKPOINT_PATH = %gin.REQUIRED
+LR = %gin.REQUIRED
+TRAIN_STEPS = %gin.REQUIRED  # 1000000 pre-trained steps + 10000 fine-tuning steps.
+USE_CACHED_TASKS = False
+DROPOUT_RATE = 0.1
+RANDOM_SEED = 0
+BATCH_SIZE = 128
+EVAL_PERIOD = 1000
+
+#Fixing a small error
+infer_eval/utils.DatasetConfig:
+  task_feature_lengths = %TASK_FEATURE_LENGTHS
+
+#Saving every 500 steps
+utils.SaveCheckpointConfig:
+  period = 1000
+  keep = 1  # number of checkpoints to keep
+
+
+#optax.adamw.weight_decay = 0.1
+#OPTIMIZER = @optax.adamw
+#import t5x.optimizers
+#OPTIMIZER = @optax.adamw
+#optax.adamw.learning_rate = %LR
+#optax.adamw.weight_decay = 0.1
+
+
+utils.create_learning_rate_scheduler:
+  factors = 'constant'
+  base_learning_rate = %LR
+  warmup_steps = 1000
+
+# Might have to ba changed based on architecture
+# partitioning.PjitPartitioner.num_partitions = 1
+
+

norbench_norcola_bs128.sh

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+#!/bin/bash
+PROJECT_DIR=${HOME}"/models/t5-nynorsk-norbench"
+export PYTHONPATH=${PROJECT_DIR}
+echo "PROJECT_DIR is set to: ${PROJECT_DIR}"
+
+
+FINETUNE_STEPS=5000
+EVAL_PREFIX="norbench/norbench_norcola_bs128"
+MODEL_BUCKET_DIR="gs://pere-north-t5x/finetuned/"
+
+CHECKPOINT_LIST=(
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+)
+
+NAME_LIST=(
+  "north_t5_base_NCC_LR_0_0006"
+  "north_t5_base_NCC_LR_0_0008"
+  "north_t5_base_NCC_LR_0_001"
+  "north_t5_base_NCC_LR_0_002"
+)
+
+TASK_LIST=("norcola" "norcola" "norcola" "norcola")
+LR_LIST=(0.0006 0.0008 0.001 0.002)
+
+
+GIN_LIST=(
+  "norbench_norcola_bs128.gin"
+  "norbench_norcola_bs128.gin"
+  "norbench_norcola_bs128.gin"
+  "norbench_norcola_bs128.gin"
+)
+
+START_LIST=(1500000 1500000 1500000 1500000)
+EXP_LIST=(1 2 3 4)
+
+
+op through each experiment in EXP_LIST
+for i in "${!EXP_LIST[@]}"; do
+    INITIAL_CHECKPOINT_PATH="gs://${CHECKPOINT_LIST[i]}"
+    TRAIN_STEPS=$((START_LIST[i]+FINETUNE_STEPS))
+    GIN_FILE=${GIN_LIST[i]}
+    MIXTURE_OR_TASK_NAME=${TASK_LIST[i]}
+    LR=${LR_LIST[i]}
+    EXP=${EXP_LIST[i]}
+    MODEL_DIR="${MODEL_BUCKET_DIR}${EVAL_PREFIX}_exp${EXP}_${NAME_LIST[i]}"
+
+    command="python3 ../../t5x/t5x/train.py --gin_search_paths=\"./\" --gin.TRAIN_STEPS=${TRAIN_STEPS} --gin.LR=${LR}  --gin_file=${GIN_FILE} --gin.INITIAL_CHECKPOINT_PATH=\\\"${INITIAL_CHECKPOINT_PATH}\\\" --gin.MIXTURE_OR_TASK_NAME=\\\"${MIXTURE_OR_TASK_NAME}\\\" --gin.MODEL_DIR=\\\"${MODEL_DIR}\\\""
+    echo "${command}"
+    # Uncomment the next line to run the command:
+    eval "${command}"
+done

norbench_translate_bs128.gin

@@ -0,0 +1,52 @@
+from __gin__ import dynamic_registration
+import tasks
+import seqio
+import optax
+
+import __main__ as train_script
+from t5.data import mixtures
+from t5x import models
+from t5x import partitioning
+from t5x import utils
+
+include 't5x/examples/t5/mt5/base.gin'
+include "t5x/configs/runs/finetune.gin"
+
+MIXTURE_OR_TASK_NAME = %gin.REQUIRED
+TASK_FEATURE_LENGTHS = {"inputs": 256, "targets": 256}
+INITIAL_CHECKPOINT_PATH = %gin.REQUIRED
+LR = %gin.REQUIRED
+TRAIN_STEPS = %gin.REQUIRED  # 1000000 pre-trained steps + 10000 fine-tuning steps.
+USE_CACHED_TASKS = False
+DROPOUT_RATE = 0.1
+RANDOM_SEED = 0
+BATCH_SIZE = 128
+EVAL_PERIOD = 1000
+
+#Fixing a small error
+infer_eval/utils.DatasetConfig:
+  task_feature_lengths = %TASK_FEATURE_LENGTHS
+
+#Saving every 500 steps
+utils.SaveCheckpointConfig:
+  period = 1000
+  keep = 1  # number of checkpoints to keep
+
+
+#optax.adamw.weight_decay = 0.1
+#OPTIMIZER = @optax.adamw
+#import t5x.optimizers
+#OPTIMIZER = @optax.adamw
+#optax.adamw.learning_rate = %LR
+#optax.adamw.weight_decay = 0.1
+
+
+utils.create_learning_rate_scheduler:
+  factors = 'constant'
+  base_learning_rate = %LR
+  warmup_steps = 1000
+
+# Might have to ba changed based on architecture
+# partitioning.PjitPartitioner.num_partitions = 1
+
+

norbench_translate_bs128.sh

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+#!/bin/bash
+PROJECT_DIR=${HOME}"/models/t5-nynorsk-norbench"
+export PYTHONPATH=${PROJECT_DIR}
+echo "PROJECT_DIR is set to: ${PROJECT_DIR}"
+
+
+FINETUNE_STEPS=20000
+EVAL_PREFIX="norbench/norbench_translate_bs128"
+MODEL_BUCKET_DIR="gs://pere-north-t5x/finetuned/"
+
+CHECKPOINT_LIST=(
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+  "pere-north-t5x/pretrained_models/base/norwegian_NCC_plus_English_t5x_base/checkpoint_1500000"
+)
+
+NAME_LIST=(
+  "north_t5_base_NCC_LR_0_0006"
+  "north_t5_base_NCC_LR_0_0008"
+  "north_t5_base_NCC_LR_0_001"
+  "north_t5_base_NCC_LR_0_002"
+)
+
+TASK_LIST=("translate_mt5" "translate_mt5" "translate_mt5" "translate_mt5")
+LR_LIST=(0.0006 0.0008 0.001 0.002)
+
+
+GIN_LIST=(
+  "norbench_translate_bs128.gin"
+  "norbench_translate_bs128.gin"
+  "norbench_translate_bs128.gin"
+  "norbench_translate_bs128.gin"
+)
+
+START_LIST=(1500000 1500000 1500000 1500000)
+EXP_LIST=(1 2 3 4)
+
+
+op through each experiment in EXP_LIST
+for i in "${!EXP_LIST[@]}"; do
+    INITIAL_CHECKPOINT_PATH="gs://${CHECKPOINT_LIST[i]}"
+    TRAIN_STEPS=$((START_LIST[i]+FINETUNE_STEPS))
+    GIN_FILE=${GIN_LIST[i]}
+    MIXTURE_OR_TASK_NAME=${TASK_LIST[i]}
+    LR=${LR_LIST[i]}
+    EXP=${EXP_LIST[i]}
+    MODEL_DIR="${MODEL_BUCKET_DIR}${EVAL_PREFIX}_exp${EXP}_${NAME_LIST[i]}"
+
+    command="python3 ../../t5x/t5x/train.py --gin_search_paths=\"./\" --gin.TRAIN_STEPS=${TRAIN_STEPS} --gin.LR=${LR}  --gin_file=${GIN_FILE} --gin.INITIAL_CHECKPOINT_PATH=\\\"${INITIAL_CHECKPOINT_PATH}\\\" --gin.MIXTURE_OR_TASK_NAME=\\\"${MIXTURE_OR_TASK_NAME}\\\" --gin.MODEL_DIR=\\\"${MODEL_DIR}\\\""
+    echo "${command}"
+    # Uncomment the next line to run the command:
+    eval "${command}"
+done