update readme
Former-commit-id: a1477208471039d3578980f929f1ca8c2a07aa96
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@@ -579,7 +579,7 @@ register_model_group(
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register_model_group(
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models={
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"Jambda-v0.1": {
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"Jamba-v0.1": {
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DownloadSource.DEFAULT: "ai21labs/Jamba-v0.1",
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DownloadSource.MODELSCOPE: "AI-ModelScope/Jamba-v0.1",
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}
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@@ -202,18 +202,18 @@ class CustomPPOTrainer(PPOTrainer, Trainer):
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if self.is_world_process_zero():
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logger.info("***** Running training *****")
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logger.info(" Num examples = {}".format(num_examples))
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logger.info(" Num Epochs = {}".format(num_train_epochs))
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logger.info(" Instantaneous batch size per device = {}".format(self.args.per_device_train_batch_size))
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logger.info(" Num examples = {:,}".format(num_examples))
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logger.info(" Num Epochs = {:,}".format(num_train_epochs))
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logger.info(" Instantaneous batch size per device = {:,}".format(self.args.per_device_train_batch_size))
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logger.info(
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" Total train batch size (w. parallel, buffer, distributed & accumulation) = {}".format(
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" Total train batch size (w. parallel, buffer, distributed & accumulation) = {:,}".format(
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total_train_batch_size
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)
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)
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logger.info(" Gradient Accumulation steps = {}".format(self.args.gradient_accumulation_steps))
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logger.info(" Num optimization epochs per batch = {}".format(self.finetuning_args.ppo_epochs))
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logger.info(" Total training steps = {}".format(max_steps))
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logger.info(" Number of trainable parameters = {}".format(count_parameters(self.model)[0]))
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logger.info(" Gradient Accumulation steps = {:,}".format(self.args.gradient_accumulation_steps))
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logger.info(" Num optimization epochs per batch = {:,}".format(self.finetuning_args.ppo_epochs))
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logger.info(" Total training steps = {:,}".format(max_steps))
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logger.info(" Number of trainable parameters = {:,}".format(count_parameters(self.model)[0]))
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dataiter = iter(self.dataloader)
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loss_meter = AverageMeter()
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