forked from p04798526/LLaMA-Factory-Mirror
fix #1682
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509abe8864
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@ -38,10 +38,11 @@ def create_eval_tab(engine: "Engine") -> Dict[str, "Component"]:
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max_new_tokens = gr.Slider(10, 2048, value=128, step=1)
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top_p = gr.Slider(0.01, 1, value=0.7, step=0.01)
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temperature = gr.Slider(0.01, 1.5, value=0.95, step=0.01)
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output_dir = gr.Textbox()
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input_elems.update({max_new_tokens, top_p, temperature})
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input_elems.update({max_new_tokens, top_p, temperature, output_dir})
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elem_dict.update(dict(
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max_new_tokens=max_new_tokens, top_p=top_p, temperature=temperature
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max_new_tokens=max_new_tokens, top_p=top_p, temperature=temperature, output_dir=output_dir
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))
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with gr.Row():
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@ -49,7 +49,10 @@ class Engine:
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else:
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yield self._form_dict({"eval.resume_btn": {"value": True}})
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else:
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yield self._form_dict({"train.output_dir": {"value": get_time()}})
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yield self._form_dict({
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"train.output_dir": {"value": "train_" + get_time()},
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"eval.output_dir": {"value": "eval_" + get_time()},
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})
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def change_lang(self, lang: str) -> Dict[Component, Dict[str, Any]]:
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return {
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@ -132,7 +132,7 @@ LOCALES = {
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"dataset_dir": {
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"en": {
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"label": "Data dir",
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"info": "Path of the data directory."
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"info": "Path to the data directory."
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},
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"zh": {
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"label": "数据路径",
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@ -475,12 +475,12 @@ LOCALES = {
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},
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"output_dir": {
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"en": {
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"label": "Checkpoint name",
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"info": "Directory to save checkpoint."
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"label": "Output dir",
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"info": "Directory for saving results."
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},
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"zh": {
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"label": "断点名称",
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"info": "保存模型断点的文件夹名称。"
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"label": "输出目录",
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"info": "保存结果的路径。"
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}
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},
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"output_box": {
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@ -87,9 +87,9 @@ class Runner:
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user_config = load_config()
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if get("top.checkpoints"):
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checkpoint_dir = ",".join([get_save_dir(
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get("top.model_name"), get("top.finetuning_type"), ckpt
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) for ckpt in get("top.checkpoints")])
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checkpoint_dir = ",".join([
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get_save_dir(get("top.model_name"), get("top.finetuning_type"), ckpt) for ckpt in get("top.checkpoints")
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])
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else:
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checkpoint_dir = None
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@ -160,15 +160,11 @@ class Runner:
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user_config = load_config()
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if get("top.checkpoints"):
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checkpoint_dir = ",".join([get_save_dir(
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get("top.model_name"), get("top.finetuning_type"), ckpt
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) for ckpt in get("top.checkpoints")])
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output_dir = get_save_dir(
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get("top.model_name"), get("top.finetuning_type"), "eval_" + "_".join(get("top.checkpoints"))
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)
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checkpoint_dir = ",".join([
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get_save_dir(get("top.model_name"), get("top.finetuning_type"), ckpt) for ckpt in get("top.checkpoints")
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])
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else:
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checkpoint_dir = None
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output_dir = get_save_dir(get("top.model_name"), get("top.finetuning_type"), "eval_base")
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args = dict(
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stage="sft",
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@ -192,7 +188,7 @@ class Runner:
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max_new_tokens=get("eval.max_new_tokens"),
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top_p=get("eval.top_p"),
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temperature=get("eval.temperature"),
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output_dir=output_dir
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output_dir=get_save_dir(get("top.model_name"), get("top.finetuning_type"), get("eval.output_dir"))
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)
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if get("eval.predict"):
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@ -242,6 +238,7 @@ class Runner:
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output_dir = get_save_dir(get("top.model_name"), get("top.finetuning_type"), get(
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"{}.output_dir".format("train" if self.do_train else "eval")
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))
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while self.thread.is_alive():
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time.sleep(2)
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if self.aborted:
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