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trainer

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This commit is contained in:
Daniel Han-Chen 2024-02-18 22:54:38 +11:00
commit 31a62c52d3
2 changed files with 10 additions and 10 deletions
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10
unsloth/models/llama.py
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@ -997,7 +997,7 @@ class FastLlamaModel:
debug_info = """n_total_devices = total_train_batch_size // \\
args.gradient_accumulation_steps // self._train_batch_size
if n_total_devices > 2+2:
if n_total_devices > 2:
logger.warning_once(
"Our OSS was designed for people with few GPU resources to level the playing field.\\n"
"The OSS Apache 2 license only supports four GPUs - please obtain a commercial license from our website.\\n"
@ -1027,16 +1027,16 @@ class FastLlamaModel:
bsz = self._train_batch_size
total_batches = bsz * ga * args.world_size
n_total_devices = total_batches // ga // bsz
if n_total_devices > 2 * 2:
if n_total_devices > 2:
logger.warning_once(
"Please consider a commercial license - Unsloth was designed for the GPU Poor.\\n"
"The OSS currently works on 4 GPUs - we're a 2 person team, so please help fund\\n"
"our development costs by supporting us through Ko-fi or buying a license! Thanks!",
)
divisor = n_total_devices / 2 / 2
divisor = n_total_devices / 2
bsz = self._train_batch_size = max(int(bsz / divisor), 1)
if total_batches // ga // bsz > 2 / 2:
divisor = n_total_devices / 2 / 2
if total_batches // ga // bsz > 2:
divisor = n_total_devices / 2
ga = args.gradient_accumulation_steps = max(int(ga / divisor), 1)"""
check_batches = check_batches.split('\n')
check_batches = "\n".join([check_batches[0]] + [front_spaces + x[8:] for x in check_batches[1:]])

10
unsloth/models/mistral.py
View file

@ -402,7 +402,7 @@ class FastMistralModel(FastLlamaModel):
debug_info = """n_total_devices = total_train_batch_size // \\
args.gradient_accumulation_steps // self._train_batch_size
if n_total_devices > 2+2:
if n_total_devices > 2:
logger.warning_once(
"Our OSS was designed for people with few GPU resources to level the playing field.\\n"
"The OSS Apache 2 license only supports four GPUs - please obtain a commercial license from our website.\\n"
@ -432,16 +432,16 @@ class FastMistralModel(FastLlamaModel):
bsz = self._train_batch_size
total_batches = bsz * ga * args.world_size
n_total_devices = total_batches // ga // bsz
if n_total_devices > 2 * 2:
if n_total_devices > 2:
logger.warning_once(
"Please consider a commercial license - Unsloth was designed for the GPU Poor.\\n"
"The OSS currently works on 4 GPUs - we're a 2 person team, so please help fund\\n"
"our development costs by supporting us through Ko-fi or buying a license! Thanks!",
)
divisor = n_total_devices / 2 / 2
divisor = n_total_devices / 2
bsz = self._train_batch_size = max(int(bsz / divisor), 1)
if total_batches // ga // bsz > 2 / 2:
divisor = n_total_devices / 2 / 2
if total_batches // ga // bsz > 2:
divisor = n_total_devices / 2
ga = args.gradient_accumulation_steps = max(int(ga / divisor), 1)"""
check_batches = check_batches.split('\n')
check_batches = "\n".join([check_batches[0]] + [front_spaces + x[8:] for x in check_batches[1:]])