devvanshhh
commited on
Commit
•
f3f9060
1
Parent(s):
6c0b884
Training in progress, epoch 1, checkpoint
Browse files- last-checkpoint/README.md +220 -0
- last-checkpoint/adapter_config.json +23 -0
- last-checkpoint/adapter_model.safetensors +3 -0
- last-checkpoint/optimizer.pt +3 -0
- last-checkpoint/rng_state.pth +3 -0
- last-checkpoint/scheduler.pt +3 -0
- last-checkpoint/trainer_state.json +32 -0
- last-checkpoint/training_args.bin +3 -0
last-checkpoint/README.md
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---
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library_name: peft
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base_model: ybelkada/flan-t5-xl-sharded-bf16
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: True
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- load_in_4bit: False
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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### Framework versions
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- PEFT 0.6.3.dev0
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last-checkpoint/adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "ybelkada/flan-t5-xl-sharded-bf16",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v",
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"q"
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],
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"task_type": "SEQ_2_SEQ_LM"
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}
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last-checkpoint/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2c057f627623a444914f327d4a98f39687a7d1ff2ba0baf7f45c1b1ce8b35742
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size 37789864
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last-checkpoint/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:22439f4525d274f28a5af57fd4ebdebdcff7533211ad59e3a06bcd8ee4e6454c
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size 2621690
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last-checkpoint/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:a3206cfea353705871f16d46e55ccf93893b489d46b83fd7ba2c4d45d71b93a7
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size 14244
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last-checkpoint/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:01c9953bcbb0cb6c86fb2f910b965b60b3698767c265429c88bfcc001fe9bbb9
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size 1064
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last-checkpoint/trainer_state.json
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{
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 1.0,
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"eval_steps": 500,
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"global_step": 328,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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{
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"epoch": 1.0,
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"eval_gen_len": 11.120274914089347,
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"eval_loss": 24.898656845092773,
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"eval_rouge1": 29.9366,
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"eval_rouge2": 22.9687,
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"eval_rougeL": 26.9975,
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"eval_rougeLsum": 27.1774,
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"eval_runtime": 152.4326,
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"eval_samples_per_second": 1.909,
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"eval_steps_per_second": 0.243,
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"step": 328
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}
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],
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"logging_steps": 500,
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"max_steps": 1640,
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"num_train_epochs": 5,
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"save_steps": 500,
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"total_flos": 2458142180573184.0,
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"trial_name": null,
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"trial_params": null
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}
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last-checkpoint/training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b5c8949174dd9b49837d8ec609d2b880bd4fe35d9d9291ea4e7c0991d5dcd240
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size 4728
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