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https://github.com/oobabooga/text-generation-webui.git
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Some qol changes to "Perplexity evaluation"
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@ -78,7 +78,7 @@ def calculate_perplexity(models, input_dataset, stride, _max_length):
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yield cumulative_log
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yield cumulative_log
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continue
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continue
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cumulative_log += f"Processing {model}...\n\n"
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cumulative_log += f"Processing {shared.model_name}...\n\n"
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yield cumulative_log + "Tokenizing the input dataset...\n\n"
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yield cumulative_log + "Tokenizing the input dataset...\n\n"
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encodings = encode(text, add_special_tokens=False)
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encodings = encode(text, add_special_tokens=False)
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seq_len = encodings.shape[1]
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seq_len = encodings.shape[1]
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@ -110,7 +110,7 @@ def calculate_perplexity(models, input_dataset, stride, _max_length):
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ppl = torch.exp(torch.stack(nlls).mean())
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ppl = torch.exp(torch.stack(nlls).mean())
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add_entry_to_past_evaluations(float(ppl), shared.model_name, input_dataset, stride, _max_length)
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add_entry_to_past_evaluations(float(ppl), shared.model_name, input_dataset, stride, _max_length)
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save_past_evaluations(past_evaluations)
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save_past_evaluations(past_evaluations)
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cumulative_log += f"Done. The perplexity is: {float(ppl)}\n\n"
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cumulative_log += f"The perplexity for {shared.model_name} is: {float(ppl)}\n\n"
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yield cumulative_log
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yield cumulative_log
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@ -126,7 +126,9 @@ def create_train_interface():
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evaluation_log = gr.Markdown(value='')
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evaluation_log = gr.Markdown(value='')
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evaluation_table = gr.Dataframe(value=generate_markdown_table(), interactive=True)
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evaluation_table = gr.Dataframe(value=generate_markdown_table(), interactive=True)
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save_comments = gr.Button('Save comments')
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with gr.Row():
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save_comments = gr.Button('Save comments', elem_classes="small-button")
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refresh_table = gr.Button('Refresh the table', elem_classes="small-button")
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# Training events
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# Training events
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all_params = [lora_name, always_override, save_steps, micro_batch_size, batch_size, epochs, learning_rate, lr_scheduler_type, lora_rank, lora_alpha, lora_dropout, cutoff_len, dataset, eval_dataset, format, eval_steps, raw_text_file, overlap_len, newline_favor_len, higher_rank_limit, warmup_steps, optimizer, hard_cut_string, train_only_after]
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all_params = [lora_name, always_override, save_steps, micro_batch_size, batch_size, epochs, learning_rate, lr_scheduler_type, lora_rank, lora_alpha, lora_dropout, cutoff_len, dataset, eval_dataset, format, eval_steps, raw_text_file, overlap_len, newline_favor_len, higher_rank_limit, warmup_steps, optimizer, hard_cut_string, train_only_after]
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@ -147,6 +149,7 @@ def create_train_interface():
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start_current_evaluation.click(generate_markdown_table, None, evaluation_table, show_progress=False)
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start_current_evaluation.click(generate_markdown_table, None, evaluation_table, show_progress=False)
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stop_evaluation.click(None, None, None, cancels=[ev, ev_cur], queue=False)
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stop_evaluation.click(None, None, None, cancels=[ev, ev_cur], queue=False)
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refresh_table.click(generate_markdown_table, None, evaluation_table, show_progress=True)
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save_comments.click(
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save_comments.click(
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save_past_evaluations, evaluation_table, None).then(
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save_past_evaluations, evaluation_table, None).then(
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lambda: "Comments saved.", None, evaluation_log, show_progress=False)
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lambda: "Comments saved.", None, evaluation_log, show_progress=False)
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