feat: pretrained by recipe v0.1.0
Browse files- README.md +126 -0
- all_results.json +14 -0
- config.json +25 -0
- eval_results.json +9 -0
- generation_config.json +6 -0
- logs/events.out.tfevents.1701268638.6c82343ebf86.774334.0 +3 -0
- logs/events.out.tfevents.1701668470.6c82343ebf86.774334.1 +3 -0
- logs/events.out.tfevents.1702138508.90c313ded1af.10650.0 +3 -0
- logs/events.out.tfevents.1702169068.90c313ded1af.1917.0 +3 -0
- logs/events.out.tfevents.1702194187.90c313ded1af.463702.0 +3 -0
- logs/events.out.tfevents.1702195605.90c313ded1af.487106.0 +3 -0
- logs/events.out.tfevents.1702196577.90c313ded1af.501706.0 +3 -0
- logs/events.out.tfevents.1702198797.90c313ded1af.526008.0 +3 -0
- model.safetensors +3 -0
- special_tokens_map.json +30 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +47 -0
- train_results.json +8 -0
- trainer_state.json +2618 -0
- training_args.bin +3 -0
README.md
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---
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base_model: None
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tags:
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- generated_from_trainer
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model-index:
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- name: checkpoints-mistral-300M-FA2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# japanese-mistral-300m-base
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## Overview
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Welcome to my model card!
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This Model feature is ...
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- Suppression of unknown word generation by using byte fallback in SentencePiece tokenizer and conversion to huggingface Tokenizers format
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- Pretrained by wikipedia dataset and cc100 dataset
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- Use of [Mistral 300M](confing.json)
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Yukkuri shite ittene!
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## How to use the model
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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import torch
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MODEL_NAME = "ce-lery/japanese-mistral-300m-base"
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torch.set_float32_matmul_precision('high')
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DEVICE = "cuda"
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if torch.cuda.is_available():
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print("cuda")
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DEVICE = "cuda"
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else:
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print("cpu")
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DEVICE = "cpu"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME,use_fast=False)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_NAME,
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trust_remote_code=True,
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).to(DEVICE)
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# streamer = TextStreamer(tokenizer)
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prompt = "大規模言語モデルとは、"
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inputs = tokenizer(prompt, add_special_tokens=False,return_tensors="pt").to(model.device)
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with torch.no_grad():
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outputs = model.generate(
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inputs["input_ids"],
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max_new_tokens=256,
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do_sample=True,
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early_stopping=False,
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top_p=0.95,
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top_k=50,
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temperature=0.9,
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# streamer=streamer,
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no_repeat_ngram_size=2,
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num_beams=3
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)
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print(outputs.tolist()[0])
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outputs_txt = tokenizer.decode(outputs[0])
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print(outputs_txt)
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```
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## Receipe
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If you want to restruct this model, you can refer [this Github repository](https://github.com/ce-lery/japanese-mistral-300m-recipe).
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I wrote the receipe for struction this model. For example,
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- Preprocess with sentencepiece
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- Pretraining with flash attention2 and torch.compile and DeepSpeed
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- Fine-tuning with databricks-dolly-15k-ja
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If you find my mistake,error,...etc, please create issue.
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If you create pulreqest, I'm very happy!
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0006
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 64
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- total_train_batch_size: 256
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=0.0001
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 4.2911 | 0.12 | 5000 | 4.2914 |
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| 3.9709 | 0.24 | 10000 | 3.9900 |
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| 3.8229 | 0.36 | 15000 | 3.8388 |
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| 3.7197 | 0.47 | 20000 | 3.7454 |
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| 3.652 | 0.59 | 25000 | 3.6739 |
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| 3.597 | 0.71 | 30000 | 3.6177 |
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| 3.5554 | 0.83 | 35000 | 3.5770 |
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| 3.536 | 0.95 | 40000 | 3.5582 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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all_results.json
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{
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"epoch": 1.0,
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"eval_loss": 3.5582468509674072,
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| 4 |
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"eval_runtime": 6274.8366,
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| 5 |
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"eval_samples": 551057,
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| 6 |
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"eval_samples_per_second": 87.82,
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| 7 |
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"eval_steps_per_second": 21.955,
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| 8 |
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"perplexity": 35.10160482608155,
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| 9 |
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"train_loss": 3.89913355111991,
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| 10 |
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"train_runtime": 393554.9634,
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| 11 |
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"train_samples": 10794765,
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| 12 |
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"train_samples_per_second": 27.429,
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| 13 |
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"train_steps_per_second": 0.107
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}
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config.json
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{
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"_name_or_path": "None",
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| 3 |
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"architectures": [
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| 4 |
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"MistralForCausalLM"
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| 5 |
+
],
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| 6 |
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"bos_token_id": 0,
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| 7 |
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"eos_token_id": 0,
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| 8 |
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"hidden_act": "silu",
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| 9 |
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"hidden_size": 1024,
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| 10 |
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"initializer_range": 0.02,
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| 11 |
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"intermediate_size": 2400,
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| 12 |
+
"max_position_embeddings": 4096,
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| 13 |
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"model_type": "mistral",
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| 14 |
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"num_attention_heads": 16,
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| 15 |
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"num_hidden_layers": 24,
|
| 16 |
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"num_key_value_heads": 8,
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| 17 |
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"rms_norm_eps": 1e-05,
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| 18 |
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"rope_theta": 10000.0,
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| 19 |
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"sliding_window": 1024,
|
| 20 |
+
"tie_word_embeddings": false,
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| 21 |
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"torch_dtype": "float32",
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| 22 |
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"transformers_version": "4.35.2",
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| 23 |
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"use_cache": true,
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| 24 |
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"vocab_size": 50257
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| 25 |
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}
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eval_results.json
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{
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"epoch": 1.0,
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| 3 |
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"eval_loss": 3.5582468509674072,
|
| 4 |
+
"eval_runtime": 6274.8366,
|
| 5 |
+
"eval_samples": 551057,
|
| 6 |
+
"eval_samples_per_second": 87.82,
|
| 7 |
+
"eval_steps_per_second": 21.955,
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| 8 |
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"perplexity": 35.10160482608155
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"eos_token_id": 0,
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| 5 |
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"transformers_version": "4.35.2"
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}
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logs/events.out.tfevents.1701268638.6c82343ebf86.774334.0
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model.safetensors
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special_tokens_map.json
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{
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"bos_token": {
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"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "[PAD]",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "[UNK]",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
spiece.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:604cb0c2f073ba13f04739ced6f8310f4f00ab344feea6cb5c4012af3876c684
|
| 3 |
+
size 1249735
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,47 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
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|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"0": {
|
| 4 |
+
"content": "[PAD]",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"1": {
|
| 12 |
+
"content": "[UNK]",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"2": {
|
| 20 |
+
"content": "<s>",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"3": {
|
| 28 |
+
"content": "</s>",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": false,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
}
|
| 35 |
+
},
|
| 36 |
+
"additional_special_tokens": [],
|
| 37 |
+
"bos_token": "<s>",
|
| 38 |
+
"clean_up_tokenization_spaces": true,
|
| 39 |
+
"eos_token": "</s>",
|
| 40 |
+
"extra_ids": 0,
|
| 41 |
+
"legacy": true,
|
| 42 |
+
"model_max_length": 50000,
|
| 43 |
+
"pad_token": "[PAD]",
|
| 44 |
+
"sp_model_kwargs": {},
|
| 45 |
+
"tokenizer_class": "T5Tokenizer",
|
| 46 |
+
"unk_token": "[UNK]"
|
| 47 |
+
}
|
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 1.0,
|
| 3 |
+
"train_loss": 3.89913355111991,
|
| 4 |
+
"train_runtime": 393554.9634,
|
| 5 |
+
"train_samples": 10794765,
|
| 6 |
+
"train_samples_per_second": 27.429,
|
| 7 |
+
"train_steps_per_second": 0.107
|
| 8 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,2618 @@
|
|
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