> ## Documentation Index > Fetch the complete documentation index at: https://docs.together.ai/llms.txt > Use this file to discover all available pages before exploring further. # List job > List the metadata for a single fine-tuning job. ## OpenAPI ````yaml GET /fine-tunes/{id} openapi: 3.1.0 info: title: Together APIs description: The Together REST API. See https://docs.together.ai for more details. version: 2.0.0 termsOfService: https://www.together.ai/terms-of-service contact: name: Together Support url: https://www.together.ai/contact license: name: MIT url: https://github.com/togethercomputer/openapi/blob/main/LICENSE servers: - url: https://api.together.ai/v1 security: - bearerAuth: [] paths: /fine-tunes/{id}: get: tags: - Fine-tuning summary: List job description: List the metadata for a single fine-tuning job. parameters: - name: id in: path required: true schema: description: The ID of the job to retrieve type: string responses: '200': description: Fine-tune job details retrieved successfully content: application/json: schema: $ref: '#/components/schemas/FinetuneResponse' x-codeSamples: - lang: Python label: Together AI SDK (v2) source: | # Docs for v1 can be found by changing the above selector ^ from together import Together import os client = Together( api_key=os.environ.get("TOGETHER_API_KEY"), ) fine_tune = client.fine_tuning.retrieve(id="ft-id") print(fine_tune) - lang: Python label: Together AI SDK (v1) source: | from together import Together import os client = Together( api_key=os.environ.get("TOGETHER_API_KEY"), ) fine_tune = client.fine_tuning.retrieve(id="ft-id") print(fine_tune) - lang: TypeScript label: Together AI SDK (TypeScript) source: | import Together from "together-ai"; const client = new Together({ apiKey: process.env.TOGETHER_API_KEY, }); const fineTune = await client.fineTuning.retrieve("ft-id"); console.log(fineTune); - lang: JavaScript label: Together AI SDK (JavaScript) source: | import Together from "together-ai"; const client = new Together({ apiKey: process.env.TOGETHER_API_KEY, }); const fineTune = await client.fineTuning.retrieve("ft-id"); console.log(fineTune); - lang: Shell label: cURL source: | curl "https://api.together.ai/v1/fine-tunes/ft-id" \ -H "Authorization: Bearer $TOGETHER_API_KEY" \ -H "Content-Type: application/json" components: schemas: FinetuneResponse: type: object required: - id - status properties: id: type: string format: uuid training_file: type: string validation_file: type: string model: type: string model_output_name: type: string model_output_path: type: string trainingfile_numlines: type: integer trainingfile_size: type: integer created_at: type: string format: date-time updated_at: type: string format: date-time started_at: type: string format: date-time n_epochs: type: integer n_checkpoints: type: integer n_evals: type: integer batch_size: oneOf: - type: integer - type: string enum: - max default: max learning_rate: type: number lr_scheduler: $ref: '#/components/schemas/LRScheduler' type: object warmup_ratio: type: number max_grad_norm: type: number format: float weight_decay: type: number format: float eval_steps: type: integer train_on_inputs: oneOf: - type: boolean - type: string enum: - auto default: auto training_method: type: object oneOf: - $ref: '#/components/schemas/TrainingMethodSFT' - $ref: '#/components/schemas/TrainingMethodDPO' training_type: type: object oneOf: - $ref: '#/components/schemas/FullTrainingType' - $ref: '#/components/schemas/LoRATrainingType' multimodal_params: $ref: '#/components/schemas/MultimodalParams' status: $ref: '#/components/schemas/FinetuneJobStatus' job_id: type: string events: type: array items: $ref: '#/components/schemas/FineTuneEvent' token_count: type: integer param_count: type: integer total_price: type: integer epochs_completed: type: integer queue_depth: type: integer wandb_project_name: type: string wandb_url: type: string from_checkpoint: type: string from_hf_model: type: string hf_model_revision: type: string progress: $ref: '#/components/schemas/FineTuneProgress' LRScheduler: type: object properties: lr_scheduler_type: type: string enum: - linear - cosine lr_scheduler_args: oneOf: - $ref: '#/components/schemas/LinearLRSchedulerArgs' - $ref: '#/components/schemas/CosineLRSchedulerArgs' required: - lr_scheduler_type TrainingMethodSFT: type: object properties: method: type: string enum: - sft train_on_inputs: oneOf: - type: boolean - type: string enum: - auto type: boolean default: auto description: >- Whether to mask user messages in conversational data or prompts in instruction data. required: - method - train_on_inputs TrainingMethodDPO: type: object properties: method: type: string enum: - dpo dpo_beta: type: number format: float default: 0.1 rpo_alpha: type: number format: float default: 0 dpo_normalize_logratios_by_length: type: boolean default: false dpo_reference_free: type: boolean default: false simpo_gamma: type: number format: float default: 0 required: - method FullTrainingType: type: object properties: type: type: string enum: - Full required: - type LoRATrainingType: type: object properties: type: type: string enum: - Lora lora_r: type: integer lora_alpha: type: integer lora_dropout: type: number format: float default: 0 lora_trainable_modules: type: string default: all-linear required: - type - lora_r - lora_alpha MultimodalParams: type: object properties: train_vision: type: boolean description: >- Whether to train the vision encoder of the model. Only available for multimodal models. FinetuneJobStatus: type: string enum: - pending - queued - running - compressing - uploading - cancel_requested - cancelled - error - completed FineTuneEvent: type: object required: - object - created_at - message - type - param_count - token_count - total_steps - wandb_url - step - checkpoint_path - model_path - training_offset - hash properties: object: description: The object type, which is always `fine-tune-event`. const: fine-tune-event created_at: type: string level: anyOf: - $ref: '#/components/schemas/FinetuneEventLevels' message: type: string type: $ref: '#/components/schemas/FinetuneEventType' param_count: type: integer token_count: type: integer total_steps: type: integer wandb_url: type: string step: type: integer checkpoint_path: type: string model_path: type: string training_offset: type: integer hash: type: string FineTuneProgress: type: object description: Progress information for a fine-tuning job required: - estimate_available - seconds_remaining properties: estimate_available: type: boolean description: Whether time estimate is available seconds_remaining: type: integer description: >- Estimated time remaining in seconds for the fine-tuning job to next state LinearLRSchedulerArgs: type: object properties: min_lr_ratio: type: number format: float default: 0 description: The ratio of the final learning rate to the peak learning rate CosineLRSchedulerArgs: type: object properties: min_lr_ratio: type: number format: float default: 0 description: The ratio of the final learning rate to the peak learning rate num_cycles: type: number format: float default: 0.5 description: Number or fraction of cycles for the cosine learning rate scheduler required: - min_lr_ratio - num_cycles FinetuneEventLevels: type: string enum: - null - info - warning - error - legacy_info - legacy_iwarning - legacy_ierror FinetuneEventType: type: string enum: - job_pending - job_start - job_stopped - model_downloading - model_download_complete - training_data_downloading - training_data_download_complete - validation_data_downloading - validation_data_download_complete - wandb_init - training_start - checkpoint_save - billing_limit - epoch_complete - training_complete - model_compressing - model_compression_complete - model_uploading - model_upload_complete - job_complete - job_error - cancel_requested - job_restarted - refund - warning securitySchemes: bearerAuth: type: http scheme: bearer x-bearer-format: bearer x-default: default ````